{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Image Data IO\n",
    "This tutorial explains how to prepare, load and train with image data in MXNet. All IO in MXNet is handled via `mx.io.DataIter` and its subclasses, which is explained [here](./data.ipynb). In this tutorial we focus on how to use pre-built data iterators as while as custom iterators to process image data.\n",
    "\n",
    "There are mainly three ways of loading image data in MXNet:\n",
    "- [NEW] mx.img.ImageIter: implemented in python, easily customizable, can load from both .rec files and raw image files.\n",
    "- [OLD] mx.io.ImageRecordIter: implemented in backend (C++), less customizable but can be used in all language bindings, load from .rec files\n",
    "- Custom iterator by inheriting mx.io.DataIter\n",
    "\n",
    "First, we explain the record io file format used by mxnet:\n",
    "\n",
    "## RecordIO\n",
    "Record IO is the main file format used by MXNet for data IO. It supports reading and writing on various file systems including distributed file systems like Hadoop HDFS and AWS S3.\n",
    "First, we download the Caltech 101 dataset that contains 101 classes of objects and convert them into record io format:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Setup:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import os\n",
    "import subprocess\n",
    "import mxnet as mx\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# change this to your mxnet location\n",
    "MXNET_HOME = '/scratch/mxnet'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Download and unzip:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "os.system('wget http://www.vision.caltech.edu/Image_Datasets/Caltech101/101_ObjectCategories.tar.gz -P data/')\n",
    "os.chdir('data')\n",
    "os.system('tar -xf 101_ObjectCategories.tar.gz')\n",
    "os.chdir('../')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's take a look at the data. As you can see, under the [root folder](./data/101_ObjectCategories) every category has a [subfolder](./data/101_ObjectCategories/yin_yang).\n",
    "\n",
    "Now let's convert them into record io format. First we need to make a list that contains all the image files and their categories:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.system('python %s/tools/im2rec.py --list=1 --recursive=1 --shuffle=1 --test-ratio=0.2 data/caltech data/101_ObjectCategories'%MXNET_HOME)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The resulting [list file](./data/caltech_train.lst) is in the format `index\\t(one or more label)\\tpath`. In this case there is only one label for each image but you can modify the list to add in more for multi label training.\n",
    "\n",
    "Then we can use this list to create our record io file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.system(\"python %s/tools/im2rec.py --num-thread=4 --pass-through=1 data/caltech data/101_ObjectCategories\"%MXNET_HOME)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The record io files are now saved at [here](./data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ImageRecordIter\n",
    "mx.io.ImageRecordIter can be used for loading image data saved in record io format. It is available in all frontend languages, but as it's implemented in C++, it is less flexible. \n",
    "\n",
    "To use ImageRecordIter, simply create an instance by loading your record file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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PWuk6TPeeNG0QKYnzju6gqL+7NHQ6KwRnibUijhRaSbyFPC9RxAilCEjSRgZCoquIJElR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\nw6C0eONoJhmR7HPlrt2MjE9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T5lyWWq3OQHmYhCoTZFOYbp2RqTFG8uO0NrbwjksuZmR4\njPndc5nOj/PStufw/BkEt6oQBiGGZkSmNUkmEZ+hSkoSmqYRKgqy/9rgcOTADoP/5ov6lqc345Wq\nLF+wkFShyAIpQ1gaRrTEWH7JJrKzuonllrHzF3fRnmll1+btzJ27gOKuoyxta2OOEmdeCFarjCUC\nKqFLwTEpW3VcyyWwHdx6mZayF0WcuSBCCT30ODHST5BW0HSDlbNzXNG6hFMnQTo+RlkNeVKCG2/+\nDF/+2i0c++3LtMcMcqrKWe3z2ffAU8QyGfy4zr0//Dl//rm/oa2xg3/8/q10dndiKAr5iWGGBwZZ\nMmsOB/v7GewfQOqW6Uimickg59I4MUGXlEAOQdICQgIC4SFkFU8+OXwpwMhwjbt/9TuWn3YqS9at\noqG9EVc4KIkMLekE7d2nseHM83hx9v0s6UiRi0kM9hxAMQxerVsk9BTpVJqGhkayuRwNTY1kMtnI\nQKNEEzOO7+PJCq8eGuO53f2IxuXUnRjTlkUoxcjGQVMkQlPFM1V8SyU/mkfXI5a4r2VQ4jnyJyqM\nTk8wOOqi7R1kdmcnvh8wPTFO757naI5pXHnRhaw9dREvvPosmaY0B3ZtJxEXmNUaRw8dwQsEv3v0\nKS66+DIaGrp44qlnicdTtHctI9PQimQkKFR8hgcHTlpb37GxXAcRKsRjOpWSGe1kQogpEnFVx1BU\nbCfE930sN4gYLVqUiWl5HkYsSYBMIKIzDs8D34sCcj3Pxw4DnBB0L8CNJZGFiAx2QUDBrhGLxXF9\nlzlz53H5VVeRbGonb7q0zOlm29atbN++nVwuxyc/eSO7d+/lyaceY3xihGuu+QArVq5m5659dHTN\npXvOHKamplBlCbQ4Fctj48ZN9O3bQ61amXFj+tEBI7zOHI+mSCKTmR+Gkb+c36f5vNkyEmks0wOh\nYNl1XN+iqSWHjETg+3iWiyYUGltaaF3Zzis7tlMsFJDDAMv2kATUa3U8xyJmxGhsaIgCp+XIASwr\nMr7jESiAiA4j08k4tmOTMJI4FRsjrpBK5lAQTJwYZX57O7oXgG/y1qWnkco0IqsaXhjQMzTEgSOH\nMeMq2bYW9u8/yPjoEF2dcwCZmz5/M/VqiYXzOvng1e9n61P3kZ+cwA58FKBULKHHUgRCIcAh2yrw\nfB+Ex2uB0wQzPpD/7k/q26p5nGKRwlQcOT/CvZ7N0rZO5vfqJL41Qk8ixquNMtWFOqcuvID13XN5\n6Pa7oFAiPp6nRTVYrSXIJ1ymZAfDrrOgrRlLqGQakqhugGS5tExXcQKPom1TCn3MQMGNG6QWLURP\nJvB2H0AdOMAhP6BimfSXp1l/0Vs5+IvHWFip0rpkJZMTo+heQEpIzGufzfpzN3H/C5sZGxtnx3Mv\ncuEll7CoexFqXMUzTWKKxu4dr3LFO6/gSH8fL217AbNQZPVZ59GSbmG6PMFIfppOL4EUhjiAGfrU\nNIm6KlE11JPW94wzz2SiUOapJ59l2869tM7pYvGyxaxas5Lm5hxuKMgXx1mwaCW7tvyWNYtmYWgS\nk9MFHCRKQYnRkQicpBkGqmYQi8fRjTixWAxN1/DxcEKDJ148TCzRQNkXDI2Oo4VihslhR9xvIUjo\nsWjOVtGolkpYgY0ptCjGLXTw6g5JRSctK/TsfIVcYxrdK6F6w7zjwiuZ1dyM59rEjAztbfNpapjL\npDlKsiNDZ1c3DY1tNDXPIkAnjJU475K5mKaHXVOpVGoEto/rBfAnpMe8Uamqhi4J/ECZcSLPjP0J\nGbfu/C9USEmSkRWBFkaxiKqqgCRHbRYnsoCn0hlcD2wn4np7rknoC3RFJRkLo5uoK9B0FT/wEbpB\noMo0trXiyRq/efhR2ufMZ7Jco1x3uP7jH2fB4sUcP96LkYhz5tln0Dm3A0WWWLZqGbKqsOaUdbhe\nyLnnns/mzc/z2O8eYdnK1Xztq3+P61kUBnr4+U9/zPT0NLIkYZp1HNfBDzyMMApxhmjP5nseAVLU\nxnBP7kn9XZddycMPPkS5UCSRTM60/BQ828V2XYQUUpqscMap57LzlV3UKw6apCECD8FrKVg+spDI\npNNYlgVhiGPZhEFA4EVGw1ASUZCJItPS1oprOUheQKVaIhaTmdvRTnmiwFmbNtGhZ9i4bC0rOrop\nDk+wfd9BjvQcJNvShFIscP0l7+axXS/SNznFxlNOIT85ztatW7n4kiuZyk/T2NTItR++Ad+ucuaZ\nZ/GrO3+JpGvEE/EZKiQR312JxqujdssM/0WEkRktDKPd3BvUf+mifkz2SHY28ZJXRmtIYWox7ARM\n9R3ndD+Fp6ToXLuGMz75cZ54bAfp7jYu/PJneeRHP6G4/wjFsRHaQ5V4RSWryzQYGt7wOGnHoznu\nkPJlVNunHQiQqaNiCgXHlXGrEv7xPKYzQmg6FNwCkzHYV5pEm9XOwy+9QDaIk0KnkrXxpZCSU2Xa\nrhDFgAYAACAASURBVDEw1k+msJi2tUv5yFsvIB1vZ07bbJYuWESmKctzzz1BJp6kZjv0D/Yze24n\n+4/3sH7eIrLTdZoVQa7okLIc1KKFEUtQrVZI6RpuXCNs0mk7yZxHgGJ5kKamFjacupqxgkVxvM7z\nI3t58tG9dM2Zy+q3dHPK0m5aupbzgvkoB3vHSCVU3DDACkAKXFQpCjHRdCNa3KsaiUQCRdVQFQU5\ncLF9mfaMQWGsxvBkH4Yb8ef1IEIgCN8n9Dx82yV0HfB8krE4vu8Rl2QkVUagMl2epNg7ijUukcxq\nCDnOknnNfO5L/0ZtqsZn//rvqLoSoZHm6S09aEGSObPOImjNkcg1IowUx8ZrjE+MUyiYOD5YZohs\neQhkvNDBFyEh3klrGyARimjio2462G6AkBVCJPwwxHYdTCsgnEk0MnQDT1EiP0QYHZx7oY0s6/jC\npVytYVourhciayqW7+ASBb0kJRkpk0IKJCzLpqW9lXVrT+XIsWOYtsexY0do7V5Ib98JMk1tLFzQ\nzW3f/xdWrVnN299+MQMnBhgfH0WWFQZO9DM4PMg5my4glWzk9NPP4IknnmDLlhdIZXN8/etfxfMt\nPN9lfkuGAwf3c9edd8w4fiPUgyxFB3aWZeHYTuQonnHBBoH/BxO0/k+qUK5w5sZN7Nyxg3JtGpCp\n12pRXJyQIZCQhcY5G8/n5Rd3gi+wLQdNi+Ixa5aN47okNYNSKXKia5r2OkjL932MmIHtOKBIuJ7L\nxMQEhqwSWi5KCHFJUJ/M87mP38iijvkEwwWK+44zfGw3hcExRNWky09S6Muj+XWevONe1l60EX1C\n4/Tzz+fbP/h3FiyR6D8xwCc+9Wl+/MMfEgQhc+Z0Mz1UjmB3rkO55BIEIKtKNG3jB68H9AhZxnsN\nqxGGr0MH36j+Sxd1LZ2h7kbhrFdd/ReM7tpD9eBBDsl1jsXqlOsnaNhd4UzxPzjn4neRL08yUSmw\n9N0XU1o2j+DYAIeeeYFZ5QrNbgyz5CILgez5VL1JXNslIalsadaioFlfoM3EgsU0A9d0USSJyXSI\nIlLETJMuLU021cpIzOX4VIFaUKOSd9GEAM+BpIGpweGJE9yz5TmS2VZu+9q/8vgTj5GfzFOxqnTO\n6iQ+exbHDu5jy/atnH7+OTSNGHTHEiQLVaYO7sP3LNTGBHnTwxkbJ5NMYZcqyJpKOFVCV94Y3PNG\nNTi0mw2dm7Bcj7YGg7SdwCNJEMaxqgHP/O55nv/dUzRnFFYtXMeLW58gcCskkjpu4CF5dTJxg1gi\nRjqdJJtKk4zH8HzQVAdVUYipIAuFjPCZFZMYGS7guXFk2SD0bALTAc8jtB0Cx0EELlIY4ka9MDTZ\nQhYhtlmjQXWQZBenXuHUU9fxFx++iiXLZkNQRVXSmMToGysTy+kk4rOIKykcV6N/zCJeMvHcKoEv\n09W9hESDoK9/EEMWKLpNGFg0JJsIQrAdGDxJbauWQxmBGSok4klCSSUQEAgBioQnwsj+77rYjo1S\nCzDrdWRZRo/p+K4f9X2J+uVIAl8IAmUGhSYJAi9Ky3FdF4TA9aOow8bmJjo72ti8eTMV00ZWdTZv\n2cbpm87jnPPeCrKC6cK6U05n8+attLa1oGkxuufOZ+HChezdtwdN01g4fy5T00WOHD7Mtm3b+NKX\nb+H48V6aWpvINWTwqxN0ds4GIZBlBc+NiIKqpqAbBrZqIxDIQkSfPwBlxuAD1pvWdsfLu2lobkRK\npVBtE0kB14uCvIUkkFUJWYJKeRIhbFy/RjJp4FgmiqrhuR5xI4UvInqjEU9QrVYxVO33AC1NwdMF\nMV/QquZwbBu7XiYOtMUTdKXb+fTHP0ZLOsP0nn1MD01RKloMjJaoOD4TakBjKk0iSJC2a+zZf4JX\ndu9G7mph6/ZXUFyVZ377LIM9Rb7wxVt4NH0PxaFhZicV5i2cTbk0RXdrN2ogU6qXcXHx4zVCXcH2\nfAhCRBDgBoIwJEqeCkKk/+5xdtgOhhBoksRo737Wn3c6h9vTHN6fov/EME7dY/xEwM9u+zUf++zf\n0NSSZXAqT/u8eTRd8DaSgcyRF7bz88/exGCxRkYxMGyHWBBCXMNUA0q+S2FaJnA9RGAjQgcvtPHx\ncLWQuu+RlBsoyjAVusya3c30dB07DKm6DlNKQEnTiNVtmvQYoRCUqmWarBpueYqJuk3v1AnaFs6G\noR76hgdJaxpxI8aNH/o4/3b/T1nT2sGpnkrjgT6e+83zLOqezwmriup3MO67zFu8gDARJ5dN8+q2\nl1jWOI+4+yeQe96gPv3X17LpnLfyyisHuefeJ6gUJnE8g1iihWQqRUZrBxGSSCfY3TeGPmst1dIY\nJ6aG8BwTTIfAjqBSuXSK5lyGlqYsLQ05kvE4qiajxhVSsiB0Q1K+xoImg73Hi4RqGtty0ZyAMOor\n4Lsmoe/g+zbgo8dU9ISPWSsQi8tMjY5x5pnr+MRf3syceR3oSUG9XiOQ44hYktPPvQr29FGoh3gO\nmJ5ACmVsoeLWJAwtyoY8duQEjZkcuWQWSQhsu0QqnaUhlyUeS2HbEns3n5y2ihZDFiB8gY9MIGQC\nEURP77JA0lRiSQPLqyELCVWWsRGoQiahGVEItGZg+1A3LUIho8UUVFnBD0MkV+ATEosZ4FejYAgi\nLvqJEwMMjo5gVkooWpxQUvjQh69nw8bziKVzHDrcQ8/R44yPT6HrGosXL6UiK0zmxxkbG2JqqsD9\nv/kN6hUyrhtwcN8ekok4//Dtb3POeefQOaeDZStWcPbK+eQaG/F9n8aGBiwzygf2PC/K3ZUkZEWe\nuUn7+IEg8MH1Tm4npCgK1UplhuLpY9sOmi5Tq9dRVR3NEAShh+e5VKtVBFAul9EUmTB8jVcjoccM\narUIBOg4zuuLuqZpVMpV/IRMOpmjbFsQBPh+QCae5lPX3cA5azbQu28fk844nmmSzTRRMKdomNdA\nd0sHO559FtlxEISY9ToEMNA/hCHBwMQ+dMUglhAMThzmYM82Pv/56zi44zmM+TLVEZ8GQ8H362hG\nBqcWcY6UQCG0Z1hIQkT6zuB2JaEizSzsb6jfG71ACPFj4B3AeBiGq2au/VE2shDi88C1RGiPT4Zh\n+MQfe29Jiu64ASED/cdZf9oprFy1gtWrV/HAfQ8zdGKM/GSJCy+/jAImtYkpLrzo7Xz4w9dy/Qf/\nAs92mLN+LV948G7u+/nPefiXd9EoC1KmoImQpmSGhKay0BbIfojq+wjfQ9UkTLeOq4LpOhxIp5gu\nF7CMBMfMKo5bZtp1KCc0TF3FlCSELyFUg3yxzIL5C1k0dyGdud2QyDI9mScsVTB0gzlzupF8n8Lo\nKFP1Gu9cfQZWfprmVAv7tj2DVqpiTCSJd7SRTKT50avP8ezDd5LWDb7x9nfTmEozMTzGLU8+8Jr+\nj79ZfW+66a94cdt2LjjvNM45+zSe37KL7//zzyhOj6AbKWLpZQSKzsh4hXhTFy42TY2zaOtegBrW\nCWsm1ekSnm0hQodKucDE6AkMdZhMwiCZTmAbgpzkEQ89vNBApOehCZlS3cQJZXTXJ3Q9fM8lcGwk\nyUNRIZ6M43g2R47vQlV9LrrgAv729u/SlIsMGgF1hKRiOg79YwE//MG99A0Wmax5oCejCZIwoF4z\nUYwGwsDHqXvEdIm0blCemmTw8K+oFA4jlBjtKz+I74Mqa0z23HfS2mZbu8iksqAn8H2FZLbEVKlO\n2bJnGPMSihYnlWkgk0mQSxnk0nEEAbqRwnQ9LMcFGTTfx61VKNsebjgTWBF4OAEETh1FDhBBBrvu\nIcfAE1C3LRQ9gZ5s4IJ3XYGsJfn1fQ9xbGCQqmkxMjxCW1sr5XKRl17ezpVXXMaunTvZu3c3Gzas\nZ1/fIb7zj9/li1/6CpddeRk/+9ntaLrGw488yK3/9D16eo6wae0iKvU6qqaTn55GVxVcz0NRZfb0\n5BmdrKJKgrVdicj9GEocGalQt73X9M28GW3rtRrpdArHsQhDH1URWHYd27Ew4jGqtRIdHR28sPUF\n8vk8wOvTOf/5IDEMw9cBY0EQRC7yICBuxLClECEpaCkN1/M476yNfOFDH0UenEAMTLO8oYvpkUGO\nj4zy6sBuOletIogleWbbc8yL6QS2jSoJisUiih6jWC5R7R2irXMWZqVEIqUxUSvw5HP3cuU3b2Fi\nX4Wxg5vZvqcHNbCxzCJyXMeRPSRk4oGKbwczuaUzaV0z/XU/eA3Z8H+n/fJT4PvA7f/h2h9kIwsh\nlhE5xZYCs4GnhBALwz9yZOv5HoEXIkshoyPDPProozS1tmCaLp6q0r1iJe9dfxakEoSq4JH7H8Gp\n19h0xkbKlTpjo2O0d3Sgt2RZ+mfvpvmM0/jV9/+Vvr0HiNWq5GybrK7TLVwSskYipqEhoi9f1nAJ\nELrO7nKRtWe9hf19vRTrFq4uKPsKU76NZqTQhMLE4AjXXPNBHvnFncxuaaNz0RK+9tVvkmrpoBzo\n/PbJJzl84AhtszvIZpKkmhqYrJYR1Tq79++hpb2ZV8qDXP3ed9N//ATvfO9bMTWZd89Oc5VyBTf9\n4HssvfhcDFnm1l/dydkbTmPrQA/AM29W31VL1hLYHjElRKiCSy86jUvffirDQ9PcdNMX2LL7OexQ\nI9e5iJHpAlqygWQuRTo9C0ODMPApizyF4ggNSR1Zb6ZtTogsahQLgwydGMQLCiR1ldCz8T0om3tI\nNy/Glptx/DhlcwG+X0NVQzTNoiHnkU2bNDdWaWuNEVpr+eLf3kI8ZoDvocTqVN2AepjhmRcn+N3j\nO9jz8gEgRq0q0ZjNUamMY2ggoyESKoacR1Z1LDPAsT1sx8c362Qyy8llljM0+ChB1YPAoVLcQiY9\nm1rh8Elpe8bFV1OuWwQolC2X7uU6oaRgeQGq71GtFOjrOUBhfIApa5qKWyCtgWfXqE1OoKrJiMpH\nSN1yMGQJT1OxAoFQVCTPQ/JNDFkijkJt2mJOyzymS2Vi8QSOorFs+So+edPfsf9ILzUvxLCgWWio\n1RJ130GOGyhejEK5xte++Y+kE0ly2Sw//+nd1Mwa5XqZWO5WvnTz/2TbSy+wc+crVCt1fnH7z5AU\nlfe+820Mjo5Tq9s0N+bwHZtAVlA1ja7ZDczKGezpnULI0Sz+iYmoXdeQDugfq/FmtZUlgWXVcV0T\nRVFIp2N4YQJ33MEwdGRVxXUdHn/sMWRZxfc9hCRRLVUJ8WfSomRsO8oqjhsxUqkU6UQS13EIggBF\nU3E9h0Qiw+DYODfeeCMf+8Cf4RzqY6j3BJl4ipe2bWNqapJCtYyryOzcspm6okTtkGwrDQ0ZQkKK\nVh0zgKUr13BocoJivo5nudRDh8bmRmQFfvrjHzJHdeg5dAC74BG6FkYuQyAHuCJADUD2ZQI36vkH\nQRDl00ZhdpEhyXNfzz7939UbLuphGL4ghJjzny7/MTbyu4BfhWHoAf1CiB4imM/2P/Teqq4jhwEj\nw4PksjFKpRLT5TKoOoEweOfbLuVX9z7EZ798C5mMTjaeYnnnfCaOn+CjV1/LZHGKv/nyl7j0PVci\npxv45r99gb++8UZ+e8evGDx4iLqikS+WGVSrCD/q1Qo3QAQC6TW2uqoyFbpcvuYU7nn+eeRkCkuA\nGYaoyTSF6RJq1eIzN3yCO3/wAxJCZvGalaw583Su/fRfcfMX/p72WfOZ1z0HPZWgf2SIcqXMxOgQ\nmUycYn6E53oPMHnYYu6yLoJzV7K72E86mEDT0jSsW8zo2BiBJtNj2MQ0jQd2bOUfv3Iz3H3nSen7\nwAP3oygCWZHwPIfQj0xEbR0N3H77bRwdLvHdH9zNqwcHaW/rwJFiOL6H4sr4joNVrFLIjyALl2qx\nioZDfbqI55fQVI/mxhbqls/QwHHq5QLZbCPN7fNZtGIxrtzI+LTFrOY5mGYJQR2zFjJwfCel8Qnm\ntq3ihg/eQCKmkEprKHLUihgvltmx5zA7946yc2+e/IRF6IUkkzKeXUaRHRS5wPRUHqtm4znQOG8J\nsZgWzaDXHfBCpFCQSnfjWXnARwkn8YMa1eIhlp72fkYGTu63+/hLL0Y4YUVDUnUsN0LnRn9DDddz\nUfQUC9ZtJPTrTAz1Mzw6SBAYJA2XerWMIgtisViEswV84UaB6yKg4kUGH9f3wVDAMMjX6liSQIsZ\n3PR3N2MYCXr6j3Osv5+xfIGpUplQkqhWSmRSaSYmJhgZGqZWrVAuldk/Mcncud3Mnz8f23M4PtDH\ns08/TXtzA1/9ypf5p+/fSrFYZHR8gqM9Pbz86h6efmozyWQGVVLRdQkzDHDNOjlDpeZE6Oq4puK5\nAcW6w9JZieg/HNVlb0bbmK5SKExjGDqarlM3bcqVEolEGkkotDTniMeTTAYlJifHaGjIoes6qqpS\nq1nRIaMkUCSFpsZGqpUqjY2N+E7UrnE9l2Q6jSprTE9M85VbvszZ55/Lr++7n05fxpwY5+jwi5Ty\n40h+iOWbOHUPmxBPyDQ0NFAJXWrVAr39fYw7dWqSYFZzM2879TR+8tPb6WybjRPUcB2fHdv2ctby\nlTz73OOsmdPBVO04ti8RmB6qEeC5LpKsEoho3j+C7ClIkhyFY4QRWykQAbG4/ock+1/qzfbUW/4I\nG3kW8OJ/eN3wzLU/WI4b2byvufrPuPeeX/GBq66mc/48lFiCBx55gmeff55d+/by4es+yuZHHmJs\ncJibv30T//DNb3PW+g0MjA7z3JNP8e5LLsUq2/ztX3+eZ55+ir/41F9xx89/zkvPb0FJRbl/qXiC\nZDyJZztIoYRmxNm5azeKpNKcUPjxnXfR3jWX0XKRQBUEno9lmihuyGVnn8uu5zbTlmtg3pwunnru\nGbykgRI3uOPeu1i2cA29J06QbWlBiWkUSwVymQSFQp6+3l6QJHzJY2B8nL09PVx46TsZGBqmoyFH\ntVbHcT0C38d3A06MD1Eql9GTSU5WX1WLzEK+9/sg7brtYBgJhCTo7lD40uev4oZPfxnTHQRSxNQU\n5vQkqiww8OlsMagVLfzAQpcCHM9HBgrTeYRIcubZp7Px0zciAo+Dhw5z4HAfe/e8SN01iGfb8OpD\ntDQ1UC5MMj7Uy0Xnb+S9V1xMOi4TE3GEV2JqcoiCqXPo+BRDUzVe2dNLf3+N4pSCLqdRwyqFyT6C\nsMDeHbup1aeiCQFh0NzYjhQux3d9BAqypKLFVCTVwbOquJ4DoU9Xh0JjNsfDfSYLOn1eOEltf3b3\nfdFIpxeNJMYScRqbmmhqbCSRbSOfnyKTTjMwnmftmlVU1BpLzzoFy7QYPbADuz6ApMqEioqQA8xq\niUq1TiAkJNWgagYIXcL3LOKqhprOcmJwmPd98INc/fEbODIyxKv7DlEu1ZDVGIahQcFnenKcdDbN\nzp37Inib7xP6EQu9tbUVx3bYd2A/kqJQrVdYv2419/zqbpbOm8PHrruWGz/5SZLZHOecvYmzzjqP\n23/2S3Q9jmPbOGaFYCbMRvJ97LoZ2dpdB3wJ1wuiwIrfjzS+KW1Ns47rROht4vEZkJ8gEUuTSCWY\nO3cR77zkMuYvWMBtt93GwEA/jmUxOT6GkASB7zM9PY1l1Uhns5i1ehR2k81FTmDXQ1M03FDmgnMv\n4NSVa3ng7vsxFImeiXGOH95PfuAoyZhOKpZEUZQo+cyykRWJo7095KUBNE2hUCkxWSwSxuIYk2MU\nBbz/A+/ll3fcQboxh0CQiTcyNFqle/UmFqxcyivDd+L5GgQqSUnHkOQIjKeE+H6UuCYE0QG7ZhAE\nAZ7nIoKZkdw3qP9bB6V/ChHy/1ee71MoFNm5ZzfJZI6a6XHw4FHcEN7+trfzng9cw9q1p7B4wQJ+\ndWKUjRs3ccbZZ9N45y8ZHhvlS7fcQiaXQdguHY0tTI5NEMqCHXt2sXjtappnz0IKQyojk7z66k6K\nnk29biLLMiu65lHzArpnt1OZGkSSoFwu4cmCCj6eHKB6IZmYAYpLz/HDnH/6BubO7uItZ21g844d\nNMfiNKdS1M0iiZiKFDqk9TiWCJmaGEPKZTh/4zkc+Nf9ZJIGKxYsRy7UiNc8jmx5lYUtc8gqBo4t\nEEFIsuqTijUgQhDl+knrSwh+4IOIIsIURWDEVILAQhISqqiSjSt8/+ufoWgGPPDwNp548gU2bdzE\n0cOHQQY5IyHl4rg1OLxvL/39RzD0yJ1rWRI/+8kOHn3wXk5Zs4q3ve1tbDz7HCQ9xdH+UZ7f9jIv\nbX2E8QGHS956IZ+/8VN0dbSjCvAdj/JUnnxhkELNp28SBooSuw4PUaj66FKWbGMLXrWOXZxi8MQu\nPH8Iy5pEBAGpeDONDbNoa+2mJBR8J0TVJBRVxnd8ZElGUmRkWQEEfb0DHPeG8D2PgePb/5NKb+bH\nG+KHLpIsIxMiey7TQ4MMHjlMpq2dU05Zh2nZtLQ2sXPXXrINzRzsHSHb0MS6897J4KHdHD92hIpl\nomtZfAMUYYAUMXTShk7ZKpNuTBFIEras8bXb/oWmWR089NQzVHyHes2iVKkynR/GMW3yk5PUqhWm\nxmQSsRi5bAZFyNRqNY5aNuNjY8zqmEUYhlimDaHM9he3k9ZlRocHyY8Ms2rpUpra2/nzaz7E2MQU\nn/rUTfyPj15LSyaNoRpYjoUcSihEkZDwOqIEiHhDuqYB9pvWVtNUGhpyBJ5PrWrjeQFLF6/kHe98\nB+9+73sYGhlnYGCQXLaBa665hltv/R6VmU6OpumIMMSyLBYsWsTU1FT0FK8ouK6L73lkshnqts2F\nF76N9avW8f1vfRdfkekd7KU4PkYagfAFzlQVTXGZnMzT0tzKVGGaRCpJqrGBRDrD+MQofiaOHVpk\nGhoYnhonMAyswEJPhwRhFeHKzF+wgMM9AxgJA6NjDu/72Ge49R++RVZTEa6E7AUEkoOPixk6mKaJ\njoxQFYJgJsvUttGVmZ3bG9SbXdT/GBt5GOj8D6+bPXPtD9bwyBiyLDjae5xkLMXxvh9gpOMITea2\nM8+mu6uLXa9sZ+fW7axfeQqf/cLf8fmvfZUdR/YTBgEHeg7w1vPOJ5QFx8dP8NG/+hgfvv4jDI2P\ncP7GTWzu6+fhBx4ktD06Zs8mX8gTTyZQDI2R8gRqg86KM1bxwtNjTJl10okENbdOXY5O8xMS1Mwq\nj+/YTEd7msMDR2nKpDCLBc5duZaJfBE/GefA5BiW7VIsT2GZZaqVMklNwRABXSsXIzdlmSiNcaSn\nhxWLllIqlFi8eDEjo2M4RhZnhhW/+8ghDh7rQZIkfnzPbwA4GX2/8uUv4QdR9N/8+fPpmjMLP3DJ\npNM0NOZY2NnG7l0HWLfhbFoaE1z4liU8+dDPuf7qz/PIIyW6Fsxj1YqV3Pz5mznl1OX8xQfOYder\nr3DXr+9gbKKIocexXYEkwVNPPcmzzz5Na2sH77jsMuYvWsafv+dCPvOJy4lrKjFVMDE6hEKN6ekC\ntZpJzbSYmPQZGLM4PGgzUAoh0YhsuARuQKU6jlcu4ZYHsar9KNoUGjaOF2dB96kYxixsW4naE0IF\not6uHwaEisB3IJBlEBqy1kjdHkVIEpMV96S1Xdw9FwDXsTE0hVKxGHHEQ2hJCNqzKi9t30d3x0ZG\nrDLTeQ9NT1IpyfSOyGQ7l3DhKW8hrkLf0UOcGOilXC5RrlYpF4u4dRtJj1GzPPRknGs//pcESoxH\nntlCrLGB4ycGObD/IH3HBihMTuNZHl2z2jBUmZ4jxxCGQa1WZ/WaNRRLJSzTJBFPUCgWcFwH1wsJ\nQmjNJWnJ6Lz3yst58flnOXP9OtaftYmh/n4+d8s3+coXb+aTf/kpHnvofpxaCcuqEUoysqYTytE4\nsi/LTJUcAAamati/j7R7U9rGNJVCoYpZN9GMBIuXLiUW19n6wkuMjufxhSAUCl2zOlm3ajWXXXo5\nP7/9doxkCsusEwYhsqxRLlZwHT+6UQqZmmnTkMuxZs06vnjLLXz5K9/ie9/5HgALly+hrbWF6fwY\nekMWz5Go5IuIUJBcuIiqEARxgwnbxInFGB4fpiGXw65VSTa2UKpU2LjmNA4fOUrFKmOkFIQf4jsu\nl1/+Tu6+737qns3Owwfp7OjkE3/1aX7yg++hawZyGGU6aIlYNHodsTiQhIRtu+SHhxnoOYjnOn+S\nce5PXdRfz0SdqT/GRn4IuEMI8V2i7dUCYMcfe9O2tnaUme1SQk8QhAHVcp2GxiZ69h/lH77xLfqH\nhlFlg1XLVvKvP/53Hnnica699jr6+/pYsXIN45NThLLC3kOHMC2P9evPoqmpGVUI1qwvRzPAYcjW\nbVtRU3HUuIHjOuw+sBfXsZFUhdPPPostTz9HtVIgUGVMyySdTuM7FlN2jUqpzqdvvpkdTz7Lwekp\nCidGcAov0pptohx6DNhlTDNibSQTcWK6iizDRVe9n0K9yjvfdyX/9tN/puwU6J88TiyrkW5p4Pmt\nW7jmA9fQN9CP63l0zZtN5/zZlK0amWz6NZnetL4trW3cfvvtDA4N43sejmMS4mNZNf7szz+AX3IY\nG59g7sJH+MxNN3Fw9zbOPn0Jhw5s5ZRVraxYs5AQl09c/27ec+X7WDhvAddddx3f+vbN7Hh1Ow8+\n9CDLVixj2dKlVMsVXnjhBebPm8dvfn0HH73het53xUWosoZr15nOj2EoKiNjo4SSQjUQ9OeL9PXp\nHD/hUbJjIMUYH56gXs/T1pBCcn2koIYiakiUkUOLes0jm+kGurC9VtDiBKKGkBR8ZISiIEsybmCj\nxAw8X0NICsnGM1h5ymns3f4Lck3twJGT0rY0MUoYhGiaghIzWDCni2XLljI2NkJDW4qeY0epFvIM\n9BxEEwqmWUKVJcyKy4QscAGPkOZsks5FS1iyejVGTMPxPFzbwa3WOdp/jH0H9nLV5ZdTqTkcO7aX\n7fv2s33fbvKTI5hVE/wQBZnVK1bw1nPPYWpyjLees5Fbf/hzZEmi99gx/CDAsiyCmQdn1dAxM3pe\nowAAIABJREFUXYswkIkZMSbHCmx7+kl0VeZEby+zu+bx+BNPUamUufWfbuUrX7iZoYE+nn/6CZRY\nkmq9imRIuLJKANT9kEQqTpMVgBAYCpTqHm9W249+6rO89OJ2xkfGCGpFzOkiYUGmXq0x3nMCNZOk\ncXYH+1/excq583jXxZfSvWgJew7sZ3pikunRCZxqHT9wsWwLO/RQVI0NGzaweP4CGrM5fnH7PfQe\nOEY8maK3v5fURAYtpnLbD25j7vy5DBWqOH5AvVZHCAnX9ZCFzPRUgWwuhx76PHj/gzz229+RTWbJ\nyml6egZwHZ94IknFLTC7ox0FuO+eXxIGPmEoUP0EA0cPs/70dQQquAQ4toMINGzbo+a4uDh4aFjV\nClo8TduSJaRmt2CbRRTHZPe2F/+YdMCfNtJ4J3AO0CiEOAF8EfgGcM9/ZiOHYXhQCHE3cBBwgY//\nsRNuAN8Hx3FQVZmaWcPQDFLxJMIXPPf0s1x7w2IWLVgYna5rMicGTxDXDOKKwS1/ezPf/MbXeeLx\nJ/B9l2xDEwu65tOUbiE/OsWzm5/ilHWreGbHNqxiBU1VaWttZffu3YjQJ5VIYll1Hn/4MS648Gw+\ndP1HyGQyPPvss+zfv59yucz09DTNLS1cefkHuf/Z59m2+Xm0IECuO8xtaKZcyGN6NpYiZih9PvWK\nTb0S0N7azHNPP8mEK2NkkmQNg5pdoe/EEebNn0NQzKOLkFu+/g16jg9QqVW58W/+Jxedu5Ez1izn\nJ3f95jWZzn+z+l757stwHIef/ewXQJS2IklQq5fZuuUlPviB69h/9D52P/gwH7/xkyiKyto1a0gn\nk6xavRJNVZGEzKIF8/nYRz/Mw799hO9+9zuce+G5bDr/HDacuYE9rx5gz+59bH/xZa56/wd49xVX\nEI9pdHfPxrNNfCEoFgv4XkC17mMkWxmZqmGGMQ6PjLHr6DSIRhxHxrKqiFoFUZ1CTUBcjeEIl2mz\nhqFrKEqcCgFNrctwaQQtg69IyEoY/UaEilA08F0812No311Up3rwXZNje75OfmwZBCleevH19sub\n1vbSyy/GD0JKpSKTk5MMDg2z98gBNmxYz4bTz+TQ0T6mp2uk8tMsXLKMsclp/MDGSMSQcCC08Bwf\n1w6xJAWr7mPaFtVajcJUkVK+wsDYIBdd9Da8QPCjH/2M/fv2U3I8jEwG3/Lo6phNY6aRmKYzZ3Y7\n5UKB0HXo7znKWzZsYPe+fRSKBbwZnCtCIKsKKqAqKq4Tgh8ihxYvbd1CU0OWV3YfwnIDPvTB63jl\n0FH279/LnXfewdXXXM3RI4c4dPggyUySlw6MUCib+F7AwaEaZ6xfzZWbFvLAI09RLFVek+kbb0bb\nWVqMdM0hPzZJu2cjBYLQ81G0NGYQMj1WxiyYbKs4zO3sJNPWwr133cWzmzdj1esooUAOQnxA0VQU\nQ0fVNUaGR9EVhUqhhOs4FKammTN3Lrf+4Pv0DQywbv1pZHPNbH95L0PjUzQ3tyBkBVXV8EKYLhRo\nbmphYHAUyw247OrrufR911EqFPntfffy9JO/o6U5R90u0pzJYFerBJJMY66BoeEh9FScpmSGA8f7\nWLR2NRe843JeePQRLCsgq6hoDihVG6PmoHgeaT2GVbVIIKP7Mk6oYfHG+BDxpwBi/l+UECJcsmgJ\niipBGBBTdcy6RVtLK7KssnTlSoYnJ/jUTZ+lobmVsbE8w0NDfPIvb0SVBB+69kP85Ef/zrXXXkvP\nsR62vfgS3/nOrSxbsRLdMOg93kOtXkEzFB6570GO9/Zy7NgxysUCDbkcpWKBTCbNJRdfwt79O+nt\n7WX58hV87nM3kc1mGRoaYnJykl27d9O5ZAE//vcf4ZompfFJ4kisXrCE/sOHiWkxtFgMTVUg9ClO\nT5HJJGhqbECRZVwlgRW6TBZHmSiMImsy733P+8iPFZgYyWNWLBKJJJqmRdmM9f+PuTcPj+ss7Lbv\ns8+ZXTNaRvtmSba8xlsWhyQmCVsISYBmX1ugJUBZCrxteQu0pYX2bXjLHqCUAG8SQlbInmDHsePd\nli1ZtiVrt3ZpNJrlzMyZOdv7h0K/9vq6EX/Xxff8NTO6rtFct+Z69JznPL/7V0CRZaIVFXzv8Sfx\n/jtNs/8B32LJQJI0lpIZfvbTR3nxxZdobGygobEWTVM5fPwAN930QVRF4+qdV/Otb36LwcFB/uar\nf0trWyOeXUaWBURBxi67zM/M89KrL3P5lW+jtrmW6ZlpTh0/RigUYXR4ismJKe67+24SNXEEbKxi\nllkjhW05GJk8ohRiYdlleLZI71CSsxNJSuiUiy6yI6K5DoqbQ/GMlTo7R6GQM0gtHCNvjlC20pjl\nEGs33gKBNvKSQEnKEyCMJGs4noiq6aiajCTY+FQPVXHQpQxjg8fJJEcJKgKSF+BU7/MXxPb73/8a\nsqJQKpfxWGl+DwSDHDhwkP6TfczNLVCVqGNicprm9lVUJepZzuUIR2IoikQ44McnCwhemaKRwbZK\n2G8etdO1IJFwHT979GdIqoCdK2Jn8ojIWJJE0XUJah6e4yKJMrIn4DllNElEUSRsq4wjaSxnsqg+\nDU9cUb0iCLi46IEArifh04LEdcgtzFIXWemEzeTLxOtq+cP7P8Hl776eW2+5mUggyHve+Q7ee911\nfOrTn6SyupK167oplEoUiybZjEE+b4KoYHmQNUs8//iv3hJfQRC8lx/9FaMDg4wODLBGk9B9ATxH\noFBymE9nyTkOhmWxrAuMLkyzXDBYyqZXrkCMAqogrcj8RBGf7iNfLuHz6yseFcfBJym4nousiNz/\nsY/xjne9h95Tp6murSWdySFKCgE9sNIZIAjImsb84iL+SJjRsQkamhp58eXdaIpGLFpBc2MDlZEA\nu195ll8+9XOqKgJEVQFJFLEtm3A4QiaTQdN1AEqRGuqb6vnYRz9McniEp3/wY5anpqltbiAQCrGz\n9SKyhkk6Z+IKMoIkgugiSS592Qw/euh//6dsf6eJ0kDAT6lcwMMjk8sS9AdIpVOUShbn56bJFfOc\n+YMzXLT1Yv7gvo+wpquDv/zyF5GAZ55+img4xOrODh7+2U+4dPs2OtuakOwSP/ruD8kYWe770B/w\n+x/6fQKqTnV1JcV8Ab+uY5VNVFXGLBr81V99kXvuuwdBEDhy5DB33HEH27Zto7u7m/b2dq688kp+\n/PDDxKMxlqxFgpEwbrGMoKtkbIt4og5sj+VMGgEXT5KJVlYjais1YZ7nIboeNZXVrFnXxcC5AcaG\nxlnd2c3CbIqcUULzhaDssrAwt+Kp0DSmZ/7DCsf/9jDNEqGATjgU5pOf/CNuv+1W/AE/Q0NDjI+P\n4YuqnOw7wWWX7OBLX/pLnnzyaUolm5zxeb79nQdobW7EscpYroNP9fHNbz7IE08/QemvvsKq1Z3c\nfuetfPvrX+Vtb7uKbVsv4+Mfv5+gP8DS4hyy4FIo5LAVB0mGfCHHwNAw88s6xwYyGF4FJacCRymD\n4uDa5RV9rWPiYiPYHoIjYJkuZj5P0SxjWhbxmkYUPUxJlkCxkXzgliQUTUYWZfzBAKIsUsynkT0b\nVXAZOL0br7RIZQVEfCGqYi2c6r0wtlkji+M4vLZ7N21tbaxes5psKs9l2zexrXstZ86e5bFfPE7A\nH2R5eoKgJNBUk8C288iCHy9jkLOKSHKZQEBA1myCQZGa6gCIMiMTC7jFLJKlU8yVECUVQRKoCPuQ\n0mns8oolsVgsrHhNXBfDtvEJPlxPwi4XqGqoYWEhiQg0NTWRXEpilS2wLZySge0Wmcy4BAJxkmqI\nXG6ZYFAg74r84uknaG5r54Gv/R2f+MznePKl3eQEjYbVm1Blj5nFNJYcQhBCeAEdTbdWisytEk01\nFRfENhAN0rV+NUZuicmhs2iaju0IpPMlMmaZHW+/honZOVa11RMYHeKV3a/i2TbpxSyVsTgBTadk\nmpQ8kZJV5vbbbueGm27iM5/5DLNT05TtIp4Aseow3evX8tyLz6P6gkhaAN0foGQ5pJJJqiorWVpa\nIl5dhSzLlIomba0thKIBrMw8ufJK4j01Pcr179pJdmEUyVwgKCSIh6vxXI+l1DKFXJaAz4fgQtbI\noUdraWtq4Y29B+iqa0DXI2zZuQEjl2FkYpRvHH6IxWQay3bxRAUPKJRWysrXXnHlf4Xvd7tSv2jT\nBnK5ND6fTj5fxKeolIrmyk0Dn4onCUiaSjqTp2BYbNm6hVtv/j22b9vOzx99mAcffBBJhCuufBuf\n+tQnKeQMHvzuD7jiiisJhMM0t7UxMDzMP33/B+SyWTKZZVRFwnNtZFlg69YtdK9ZzcM/fwxZljFN\nk8XFJRoa6rjiiisA2LNnD02JRopmEUEUWF5KInoeW9dt5MTRo2xcs46iUWBoaAjdpxGJhYnFo8iy\n+GYCTMayLSRdxVM85peSLC9nqIxVoUgqC+k8giBSKpWAlQTcb/wUZ0ZHLmg1+dRTz9DR0UFrayuq\nqvzmdfL5Ip7ncvz4KcbHx3nwwQcpFArE43GGhoYwTZMtW7bw/e9/h4aGOiRJpFg0+cpXvsLw8DCp\nVIqJiZWD3jXVFYyOjvH3/+tv2Lx5E5Zlo/tCZLMGui/A+MwyD//kG5w4dpCGlvVUt1/HmfMKSqgS\nTXcpZJeQRRUPjbJdQpZs4lEfTt7EynosTo+zPPMKOTODabtcdOlNiL4uLCWGq4l4WhlP1dBFD32l\nrQHF58OxS0ilBabOHiI710t1ZRC/T0QUPCwbjh1844LY3nzzu0ln0hw+dBTLdpBEkXXrVnP99ddz\n0fqN5HI5ek+d4gc/+BGyquF6HtU1CaqrE/h0Bd2v4Pf5CAUDqIqIVS7i2hap1BKjY5OY+FhaSDE/\nl6S6MoFlrfRZRiJ+BM/B8VbKmG3bpmiayLJE3sgjCAKRSAR/0M/SUgrXtdm6dStzc3OcOzdEPB4j\nn89jla0V+6Gksf3iHczMzLMwP43gFqlLRPFpInWJev7m7/6BNw4d5clnnuP4iZOEgn4uv/RiFuZn\nmU1myRm5Nz+biOM4qD6FcChE37Ezb3mlfuJ4L3a5TCjgY/7cWbK5PMFoBU8+8xy333sfpwaHKTsu\nP/zxD7jk0ot57LHHuPmWW9i3bx+qJGMWisiSRMmRaG5tZnE5RTqboa6unsW5eaKhMBMTo3hSmfde\nfwOK5mc5bbBm7XrWbdiE4wqogk2pVCSdzREMh/GHwyyl00QrYsiKwv/4w7tBlFm7diPlQpHxc/2E\nVIvOxjjxWIyBkRlcBNKZLJGKGJriI7ucQUIiXJPA0zT8sQo+8J4bWRgc5ZXHn2ZoaBBb8MjpHqqi\ngSAhyTJIMsgSWtBPc2srv37isf//rtTT6WUsq0TZMrEdkULeQFMUBMfDLBeQVAVM0GQflixy9NBB\neo4eonv1aj7z6U/zwwe/i1UuUV1bTXY5ya6XXiGowNzECLWNTZw6mSFWU0t6OYPjWOg+nWLBQBBs\nHMflVO8JcpkUhmEQiUQwTZPq6kr8fj/Hjx/HcV2ikQip2cUVi5osEtT8LCeTnOzpIewP0t93Cl3V\niEbCpDMpOqpasVwLy7ZRVZlysYSoKiunBFyBdCZPY3MbF23eSnJ+ETWVZm5uDs+zcV2XcnllP1iS\npAvmG4vFOHXqFENDQ6xbt45EIkEgoOP363ieR/uqVt7Yv5fz58ewHYd0JsXWbVsYGhpiYPAMn/7M\np/mnH36fUChEqVTiiiuu4Pjx43R0dKxErf06uewyplmirrYOx3ERRZl8Po+u+zhz+ixf/+YPKOdm\nqAjpqILLmd7DVDRfSaZsEIhHCQfqKVkeqeUitgCCIpO1XGRFQ4go6G4TbmAH5FMEZBWpahWodYhS\nAE+xQSqhyD5UbCS3jIiLjI1bynKu9zClxRGwTJyyD0FdKYrw+y7cgPnqK68hCBLlEniegAP09g4y\nNDTF7be+n7Vr19KxqoNrr72GXz33MuFwkKnJSaanZwiERTQVAv4gkqTiWgKKrJNKpolVVOIRIZ1Z\nJBQMU7upDgGPQiHP7993N65bxsilOXFylF2/3kVLSwvlcplsJoeiyFRWVrJz507Wru/ma1/7e7q7\nV9PR0cG6dev40z/9U775zW9x6lTfSgpTgFA4yHJ6Gcs2KZoGIb8CnocoiEzOTPGNb/wjf/L5P+Pc\n8DBnTp8mFo3y4guvokggKSsBPlVRcVwLu2Thk2Tyy7n/kt9/NsbmZhkaHUHXNYSiRayqkqlkmmPn\nz5N/6inOT01z9bXXYjgWu97YQ2NLE08/8xTBQJD5dBrPcQkEAhRNSGcyRCpjyLJKJpMlGAiyOL9I\nLpsjVhXktV276Fq9hnSusKIYlkW2bb8YMLFxUXwunlDEsURy6XnOjw0yPz+P5BaIxxvILi3i1/wY\ny8t0r2ulq6mJheQitYlqBodH8If8FEsmsqySzxfQZI14yaRgl0jU1zF7/jxbNm3l1KGTIGuIqsj4\nzCg47sr2mifjOgJlx8Z1CsxNnP8v+f1OJ/VCoQCCTblQQtEC+AP+N0t5baxSCbtoogZ0SmYexxKQ\nRA8JgVOnern/jz7M//zCFwiHg8zNTOJaZc6PDlEVjbL9ovU4yMxn8+zfuw/bsikWCnieTVtrE/X1\n1fQcP0xLSyMjw8M0NTURCoWw3xQRLSwsUFtbi2maRMJhBCWIoqmcnzyPrirYnocjitQ3N7Nj2zYe\n+eeHqKqt4p3vuIoNF20kk10mubxIMplkfiGFUTBZSi8TiMUJx6sYn5ln9QaHhvY23n7tKhbm53nk\n0UfJ5XKs7upEVhREQWB84sJcgl1dXTQ3NzM1NcXRo0cJhUI0NzfT0bEKSZKJx2N8/vOf533vex8P\nP/wwP/vZzzh27Chr167l+PHjHD16hC9/+S+Zm5ujVCpx8OBBNE1jYOAsILB582buvONuHv35w8Ri\nlYiihGma6L4gqdQy//AP/4vW1rUU0h6tjRGGRmepT7Qh6mX0SITZ2SkUxYeqR9BUDct2KFk2tlBG\ncFxwZaRwgIqaHQTcEr5gEMvTsVwfnqQgKAKi5CG4GqIg4BbyxMI6c7MTHN3zAh0NYYoYxGqqmJ2b\nJR5spmCaSMKFNvOAKGorkijfSnONruuYpoltuTz88C+47fabSSRqefd115Evlujv7yeTMZAVj/RS\nCVUTyKRLCMhoqk5VZYCOzm6O9/QSDocJRyoYHRp683do/PjH30NVJMbHRxDzHla5xMUXbyOXy6Eo\n1ZhmAU1bqZ17+umnOHDwAI2N9SwvL9PX18fmzZtRFIVf/OIxvvKVr/Dqyy9Ttkqomk65XERVRfx+\nH4LgYJpFFEXE9jxKVolvfuMf+dM/+3O6O7t44smnSC8lwfXAM5FEibr6BLWJOuLxKvAEFhaXGBl5\n69/dz3zqs5iCw5U7r+KD7/4AtfX1HDh8kFWr13Hzrbfx7W9/j8W5JPOLCwiih1Mu4+QMzFIJWZRw\nBZA0BbdQxrEtBEEkGAoiCiJBXef86DiKrJCan6e5vZOAruN6HiNjA7ztysvY/8Zu/BGFwaEBJFFC\nUzQikSjhUITlxRlCug8HuOrqnQwNTXO2/yyFksvZgTHWtTYzPTmDGwhguzbFXJZAMEIylUKSVwKA\nMWxi/jBuscDR/Qdojjew7bLLeO655zg3PkJOs1BUBckVQPRwRTBdKHsWgf9Ga9fvtqO0rpZLL9tG\nIlFDrmihqxrLCwuoqoLjWIQiQfrPnubw4RPYloMogCt6SIBpFvnpTx/iPe95D2vXrWZwcISCkeXS\na68l6NMoWAIBn4/UUgrbsvD5fOSNDIVCntnpGRrqG8hlM7humc7OTs6fP4/rrhQuO46D3+9HkqQV\nDWrQT8Gx8QI+losFLrp0O0FV4cThY8xMTbK+u4tEbQLBcxg5N4AWUKmtqaK7uxNVj2I5HjNLSR56\n5OeMT07hCwQ4c+4csWgFcr6EANz7wZvRdZ1iceXSMRAI8PizL1wQX1leeZ+uri5qamqYnZ1lcHCQ\n0dFR1q5dS1NzC7Zt093dyRe/+BckEjV86YtfYmFhns7OTmZmpjh+/DjDw8Ns2rSJ+++/nzfeeIOe\nnh4uueSSlRWLpKFpOvl8gQo1giwp5PMGw8PDTE2fx3M1KnSHkqHweze+l8uvu4dn946w/8QUVbE4\nirziwi7YZTTKeJTQFA8lsJJckSSZghvAr8cpuWC5IoIiglBCEssg2EiCjoSLRJnFqUmO7v01mlgk\nAJjFeXQpgIRLLpMlGAqgKOoFf3cdx8WynDer/SCXM1BVFcsq4yrw+JO/4pN//HHm5xdZu7abbNag\nkDfIF4oI+CgVBDSfSk1NNa7rUCqX6B/oZePmLhKJWiYm5xDFURDgC1/43Mp2l2fT09PDzNQkoVD9\nSjrSthBFgVgsxtzcHLquoygyS6kkF1/yHsbGxpiZmWHv3r08+eRT3HPP3ezYsQNJFNnz2mssJBcJ\nhoMYeYPW1iZkwaWUN3DsErWNrbz88j6uufpyzvSf4ob3XcfwuQFamuo5cOAgV1x2OS2tLSwuJCkW\nS5RLRQRBRlcuzDBadMvcdccdLCzM8+PHv8+999zH8Phpdr59B4cP7Of3776bj9//ccSciSR6+CQZ\nPVZDqVSimF8pmdZcEaFs4Nc0yKdx3BIF20IKhwkGJIw8VCbaERWRoYkBCsUCgWCAY8cOMj29QFAL\nUBmPY5omo+PjK/+4Azpzc3O8453volBQWVyymVnOY8o+PvXlL/P0oz9mz8AApTLUVdUgKCauWUAX\nFDTPwymaVAQqyNsaR3YdwF8RI9G2iv6BPjZefDFKbyU7Lupi60Wb0XwqlmViWiauCI4kMDw2xpED\nR5js7/tP+f1OJ/V7P3ATiUQNdXW1zKczVFVWrohsBI+RkREqolHOHu/hvltuZf+RE5zrP7Mi5PJE\nHFHh/PkpXtn9Gt0b1/HqnteJR+OEaxtwFA1BKHNw1y7O9R1DllUi8Si+kJ+0WWAhtYTfJ9Pe3IRZ\nOM/hfYcwyyaO7SCpMpIgYeQKiKJAvlxENlUcM42VWqK2oYX3vv92Bk6fRj55ijIWAzMTpMsZJK+M\nIDggiOSLNgVrpXtwKWcwly0ghSoo2CLF5Sx9h47yhT/5NMG5OXbv20frunUYnkfBLhOtjFFfW3vB\nfI8cOUo8HqexsZGqqiqi0ShNTU1MTp7n5MmT9J06zfr162lubsRxbG6//XZeeOEF9h84wKr2dsKh\nMIuLi/h8PgzDoLKykrvuupNrrrmGuro62ttXMTs1R1VlgnQ6SyQaQRBE/H4/+bxBbW0thpHmure/\nA6G8xOjQGcYe+jZjaT9j4xaOV4ldTCEJ4FMiqJJIOjdL05oEqfQcmXSa6rpWAr5GPMdDVUOgKJSd\nAlDGdUsIrovn5lEoUs7OcnTPi5BfoqGtmvTCKJpoklyYJBjwk82mCYaDFApv3fX9m5GoraKhvg7N\np7OUTGKaJuMT55FlAcfzMIwcP37oIdas7uLee+/m4/ffzze/+Q3e2Pc6JVMjnS3j4TA3s0Ag7CMU\n1lF1hUPHjhCJBigX5De7KiVOnz7Ndde9h29/85sUTZOqWBWmWSQajRAIBEilUjQ2NqDrfpJLC7Q0\nt1BVXY1ZLNLY2IiiKJw7d45Uapnp6Wl6enqYm5lhcXERD49UKkkiUY2iSMiIOLIEksbpgTE0VeXF\nF15FVxUqQjr33HUrx3t60DSJxkQF7a1NHNy/F5+uY5VtRFHm2NFjF8T2c//jszz7zDOYRp77PvYH\njI2P0X+6n86O1XR3r+F73/sunufiD/jJZZYpY2E7NoFAAFESKZfLFIoFwCOfN0DwCEVCmGUTI5/D\nNItIigyKTE1tLdOz50kllyj4S+y8qo3+3jOYap6JsZVtyfJvfPZ2mU2bLyK1vMSqrtUcPHKE5XwB\nTxC48YM3U1ddwdkTB9n96qsIskKhWEIRZfK5PBX+EEa2RCKRYP/+fYiyQtF2yZfKnD13jrrOTt5/\n6y0Mnhvi9Jkz+Hwa6VyGhaV5IrEKJF0jFA5z9bXXcuKVl/5Tfr/TST0YCtDdvYb5hXkcy8K2LPL5\nPJIIPk2jUCjwoY/8IfmCyZkzQ2zYuI6enpMrK3bPxSlb9Ped5Hvf/vZKSMAT+dZ3v0vAH6Cysoq+\n/tOkc1lKjkIqmUSQBcp2CVGSMM0S54aGqa6s5uLLLmcplWJ6epq5hUVC4TCrV3cTj8eZnZ1jbGyO\nfM5A9sC1bX6961X6enoo5/MgOGiBILgOZjGPIq0cgQqHQgRFDU+WmVw4haJp5IwsgWCYeChGZ2M9\np/v62BaNguMwPDCIFwqQLZuMjI3Qr134n+byyy/HMAweeeQRrrjiCjo6OohEIsRim2hsTDE5Nc2B\nA2+QXFpNZTyO67q0tDRz6lQfo6Mj6D7tTbnQStQ8EokgCAKdnZ0rbUiqRldXN8+/8DxzswvU19ci\nvqkilWSZSCRMtEJlcWmBmpCE368wn50nndEQpWoEIYxTzpHPZ8gsFVDxUOU8Zw6e46YPXMMvf3mE\npcIcW66qon9gkkTLehazKUQd8CxUUV5pwfHSkF/ixBvPIZaShEIinrVM9+pGAlKM3oFxQlE/M/NL\nFEzz/5OV+j333sa73/1ubMtmdHSE+vp6jhw9yhOPP87ps6M4jsPMzBwf+fCHeNe73o2Ry/F7H/wA\nbS1NBIM1/PBHP2NkbIi29hYsp8zkzHkkVaS5tZm8UcCwDHw+jeV0gVdf3Y1plrBtAVkMks/ZqDqk\nUkt0dXWRSCQYGDhLLpchHqukbJVXekKFlWxCdXU1NTU1TE9Ps2/fPkRRZGlxkYqKGKs62xmbGCUU\n9rN921aqKyp46vHHmZlcxCirlItFFFyef/YVFNHhjz/9Sdav60KUHQbPnKKppY4//bPP8p3vfIdt\n27awuLiA461maKrnLbP9hwf+nrBfJ6T7eeqpZ4hGYtx+2x0sLS3zyKOP0Nt7AjwRWZT8S8W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KShqCq1tbV89nOfY/WaNbz48kucOzeEi0hLYxN1Wy9n59uvoaa6luXlJJIsIMoueAqeKFHX2M7R\no8e45LLtJGrrmZ2bZWp6nmIpQzAQYHF2BtcyMTIpaqqi1NVVMT45zuDwKLpZJuwKXHbRVg4dOYYc\ni1JSZCLxCna+81pOHD+OWS6xe9duWloaOHxgH+FIlIamdhrqmsgUbGYWUlRG4yixKiTb5Nqd7+CN\nJ37xH6ED3vqk/l3grzzP8wRB+ArwAPCh3/ZNfvnkk7Q2NTI9eZ70QoY1qztYu24Dc8kkY2PjvO+G\nmzjR28fk5HnKnkhVIEJtRSXBJh+N9Q3IusbZ4XP0nz7FbXffyfRiklf27cHv8xENBDEWUzz78mPs\nO7iXQrmEK0EhXyBRm+DibdsZHxtncX6e7du3gihy5PBR5s8OEQyG8QSRJ578Oa7rUllfzcc//Dk8\nu4jrWQhIKLKEaWSZLZtctHoNEd1PPr2M7dgsLac41NuPLxwhb1g0VNdTzhpUiB5rV3cwND6BIDqU\nXIea2moKySWcfI5dr+9Fi1exZdvlrFu3mbvuuxNg7q3ydT2PM6dPc++995Iv5BGElZtrq1evxrZt\nRAUUWaVc8giHIpRMCOgxahJVvPbrA8Sr4tx9932MDg3ywrO/JBDwoesqC8kZGgMak1PDVMbr+NBd\nd/DLJx7HbG/EjkYIBnUQPHwBP0Q1Tk6NY07MkjM1Gldto6qigULJg9wSRauMYVu4joQkqVTFYwTC\ntVTWraW1Yy3+qgjn/dUMLweIhqPk7UlE0yKkqOjFJezkGAo2omARDvqwy2UEdNrau5ifmVlxoygK\nt93xQVo72+npO42sigwPnLsgtp2rV2NaIu957w0szGf45x9+m4P7DhPyh7j0ki1s3LSe/fsPMjIy\nzsED++juXkNv7ynKJRtZkjCMHOVyCRBYTqUJB4Pkc3m6u9dwxx13sGHTakrlEocOHWY5tUx7+yqi\nkSif+ZM/IRgIoAdVCvk8jutQWRnjqqvehqr5EASBM2fOsnv3bm688Qb6+/upqqoiEo0yNTnJqVOn\niMfjWLaN6/0mK+IQiQTwByTMUp7xkVEcyyFSEUdTLBpamrEEF9d1WMgsU13XQGNrBy+/tgvX87j0\n8qs4eOANLr1kI5/99IepqolTXXc5b5XtnXfcjaj5Wbd+E8f27SWXyzE5OcmGDetQVkn8/Oc/RxZF\nbMdmYnKSTRddxIkTJ3joJz/jHe98J88//xyOYyNKOp2dnXzlq3/L/PwCv3r2V/SfOcPI2BjhYJib\n3vd+Nm3ahqrqHD58lE2bN+IPapw+e4pS0SAQCCNLCl2rV7OUylIRr0EPhpBTaYxknnDAz69feYm7\nb78VXRN54YVfkkgkmJiZpaOzg6DlkZ+cYXxsDFlRUFQflgjXvuddvLZnD4ODA2Bb5PNZzGIB2yox\nM32e1197nevffzOTsyM0NTQT8OucOXea9vpqFL/+X/J7S5O653mL/+rpD4Fn33z8W3mT+wcmCIeC\nRMIRWtqrKeQNXnrpJVpWdRAKhzlx8iSJ2no2bd1Kd2cnbirHeM9pMC0WxqZQK0LYjscVV12F7vNR\nKpdobWlmw7r1fO0rf0sxmaEyHGX7tq14ssjg0DBbtm8nGo/x+p6V7YZLL7mY3p6TdHR1YtsulmWD\n4OE4JZqbG7hq5076B86w5/XdzE9PkkjUYpZhcXIKWRBoaGxAVERs28Ln04j4K5gvllhILZErFVHl\nAO+/8QOkpodYs7ad2ckJymaBQCBAXbQSKZunYJfxPI99h4/QOzJKLF650qhzoXzP9FIqlXjxlRfQ\nNI21a9YSDIVAXNlvDPhD+HQ/sYoq8ERsy2Fy+jx7Xj/Aqb6TnDnbx9VX7+QTH/sIH/2jj3LyxDFO\nnOghn1/mZO8iDY3NfPfbD1JdHeeOW2+la1UHut9P0XIQNT/JjIEVCZEkRN72sWHHO6hOrMKzJHxl\nj5hs4eg6RddH2RVA8lEUPGxNR1BbMCiTV1Qsoih6FMMs4QKuYyMIEgEJ2ptijJwsoSsisgQIHrLi\nMjkzS1PrKqYnZ/AH/Bw6cpi9+w8zPT1LKPQvWuO3zPaf/vklVM3HgYNfZWJijOWlNB3ttaxdW8cV\nb9uKrgdwbZPmpnpef/0ATU0tFAoFJFHF8cCzLBob6wmHIgwPDWMWSmzfuonvfe9B2tvbsCkgiCLb\ntm7moYd+gih67D+wj6amRjzHZevWS5icGmN0dIQtWzdg2w7BoI7f78PzPD74wQ/ywAMPUCiYdHS0\nUS6XaWhowHNdZmZmCIXClCwLTVNpaKijrq4S1zPwaVVsXA89xwdxPRsBFz2gowcF8rkSRrGAs7TA\nYtZgbn6eTCZDJBojtVxm16697HrtGBUV/8J3+1th+/zjj6P5dH70j19n7caLmF9MEg6FAYGy5dDa\n0s7IyAjZTBo9GMTnD+C4HsupZYIBnc2bupmYGOG2O2/k5ptvY+8bu8kVbHbt2ovtSoSitVx88Q42\nbLmY02fOYmQzBIJ+BgZ68et+5mdmmJsfwh8IEK+sZd8bb/D+D97KcmaJvGkQrPATzYTIZ1P0Hz/M\nZz/+Bwiewb59L/Phj9zP2aE0Yb+PiCdTEiUGBodAVnEkCUeWePc7b+D5559HFv14ikNVbSOHT5zE\nLpv4g37OT40xOtRHU3U154YGGFucY3L0HGP9Ev+doPlb8qkLgpDwPG/uzafvB/rffPxbeZOv2XE5\nAd3P3Ow8R3v6CIVDxGrqaF+9njsu20FdbQOFXIGe06d48cBBFFFmcnGSRLwSPRxCcD1GUyle7j+B\n9dKzfPrDH6ajoYb9v36VetUjsW01VbUJ/K5NwfEYx2by/CTxRCNXXvUetm7YSDwUZfs113P09X3c\nessG+k73kXeLtLQ0YiwtMT86iqouk8wmMVyD5flFEsE4HZUBGmIt1FdEqMQib+TxByMYZpmSK+Kg\n4ngldMWlpipEMu1jcmISM5dD8kcxigI2GgPJYSoqqhCWMlQLATZvv5y1l2ylNlbJd7/3jxfEd9u2\nS6mtTZDJpGlubsbn00illmhoaKBQKDA9M8/i4AgzMwvMzy1SKJgsLa2cuc7ns2SNAgcOHOKNPa/x\niY99hHe+YydNzY08+dQTDI+N88wzTxKPVHLqRA9/3nuSj97/cT76iU+xbBpMLRokcw75bJiqpovY\nuu5ibDlEuDJBSIaAW6C8NEvKcsgupghG4mTMDJ7so2StJAJtW8EulvFbWdyCgyR4CGqRsmUjiCoV\n8QiCWoksC4BNuWximiqm6TA3u0A0EqQ2UU9yboZEIkpHWy0f/aPfX0nunRu5ILaRUAU/efhRtm6/\niHQmya23XkckKNPcnEByy6xbs4HQfXfx/AuvIAAH9h9EkhRs28Gvq9huierqStpaW8nn0mzetIkb\nrr+e6soQ5wZOUlVXQSgcxXVMzEKavCEQDurc/IEb6e3tpf/0SRYWZ4nFwoQjPhKJBHgin//8pzl5\n8jTDw8PIsoRllRkfn0DTNKanpymVytTUVGMYBnowzMLiAmG/j6XkHMGggCTJhAMrfhlFcAnoGj6f\nTiweJBLWUVSZjGHgeh6FvIHrujzyyKPcc/c9tLc2sX59J4JQ5sEfPM5bZbv1iqsJBkNsLpd57LEn\naG1tJVZZS1//OWRRIhKrQRj/v8S9d7hkV3nm+1s7165cderk2KdP524JISShnIgGZCwQGDAY/Fzj\ncRiMjW3suZ7ra4/ti2fssT3BHmPDJY6xSBIgCYQVAOVWS+qcT86nTuWd9173jzrdFuZeBOq5D/t5\n9j9VO9Vba3/fWl943wWyxV5Sdo4z56bJ5krMza9w2eWvIJfLsXP3Hm67/XU89PCjzMwvUK21ufa6\n62k7PmbKpu22eOjR+zANjVqtxo37rkfT1G4COTDZbFm4Ycg37r+fwcExTp88iev6qLrC1I4pdF1w\n8OBT/MIvfADf9/nEJ/8B3wuRQmClLQI/oO16tMIOVilDu9EGTUNRNYq9BZywQ6aQoq9SobdSolws\n43V8Wu02hVKB2Zk5BofH6O3tZ+eufbz2zXfx0MOPMD42xP1d7eL/z+3l8qnfIoS4HEiAGeCD8OPz\nJu/Zs5v7vv4NVFXlHe99Fysb63hhxJnZaXygurrOyOAwURwz0dOLruuMlXsolUo8+eQTPPX008wv\nLpJNpzEU+MeP/wMDuQz7d0zRv3Mnqm7ghCFep0mht49KqURa0fnHz32WwPU5tG2KUiZPaXICNQxZ\nOXWSk+dOIdMa506fIKWqjPX2sRmscubsWRQJkRugtSO2D4ygKyrNRhPV7WBbNmEcs7K6gcyXmF9Y\nQMkXCAOPZn2TOAxY3lwjb9vEoY8UMQuLs8SqyZOnTxLFCZ996B6qFtz7ra9x7vTF0qWbXi6+pmky\nPTONrmv8/Sf+nr7eXiqVHuYX58lmMmw2m1x99atZ3dhk2/ZJBgeH+e53H+PI0RfwwpBcrkir6WAZ\ngkpPL54XUq2usnfPfnTLJokFpWyZtY01EqnQcCOePXqerz7wMDPLm9z4pp8jNMaQRoa2b+N6EMkm\nOc1lvKyx7xU7UAKbWt2h6br4CJ5+7nn8MCGTLSIjiOIA3dhABg6qqVBtrGJZPcR+QG9/BVsZJkok\nUnTVY3zfR0oYGhrikW89gCoEzWaDP/qT/86VV+zms5/9J44fP33J2H7jgW9x222v4ZvfegDbNhge\nHuGyfROowmd4YJR8rkSpXEYROqqaoqcyTJRoLCyucPcX/yeZTIZbb7+VW2++kb/+qz/nP33sT1hY\nOM0n/uFprJSFZuvs2bOXPbv3YaU05uYW2L/vMnp7+/mZO+/g4Ucf52Mf+w+Mjg9SKmcoltNoqolu\nCN79nnfw5BPP8Mwzz3DllVfywAPfxLJMstksQbBJvV7HSqUQoks6t7C4zBtefxWqcDB0k6ltFZYX\nNlltusgwIJ/JUqn0YFt9SGKKjsvffvIBjpyYwfNC/v3/8V84d2aJtWqD7/3yY9jpiyGCD78cbKMw\nAQHf/d53ePvPvoOvfOnL1Bp1ekolPN9nem4GoaoUixmCThORLaBbOv1DfZybOc8N11/Dtm3jfO3r\nD/Doo99lYXGZO37mToIwwI8CTGFzfuYspZKJqmosLS3gx01838VxHHRDwzDTeJ2QgeEhCrkCIo7R\nZIJTa7Jw9gx2Wufg49/ltz78KwwNDXHwmYM0Oy3++eFv44YeAyN9NFs1soNZrHyKhSN1lESCqtFy\nW2zfvY3VpXkS4ZHOmJTyZaxyjoW5JQrlFOtrVZ584in6+ofodFaYmV5hdGQ7qvLS3bo/SvXLu/5f\nPv7kDzn+T4E/fck7A4qmsGffbs6cOc3M6hLLK6sUSmVyhTzbJyfIp2x0VPADzh16ngTJ/PIywxOj\nnJ2ZwfHalCtFSrpJ2GzxmldfS2/OxgI6jTZBGKHoGqqqUFtfZ3x4mHRvP0Io9JUq7JqYJHQcFjbW\nMfUULd/luisup5749PT3kDZNHn/4Uc7On8AyDHRFI5PLMNzTx2W792IrOjLw0AkxhEoUJ6RSNvMb\nVdKpFKGqYAoFGYfESYSiQCaXoZNIVA2GR3p51f7dbBsdg0Dh1z78EYojwzihT95KccWBnUgpf/rl\n4tvudLrcISmL22+/HdO0KBRyrK6usFGtcvV1r2Lf3l3c9fa3k7KyxHHEqVMnKBbzNBs1rHwaYeno\niuSVr7yaqd1TVFeXOXLkCLfctJ073/pOHnjgft7X/wG++o1v8e3vPMWan2JmtcPAxF46AURxisgH\noWoIKWk2OgSKj1NzmD47Q8ZL4zR90ODAKw8wXqwwsW2S/nI/q0tVNmrrPHfuCGlLp9Oo0TuQo95M\nSOKIlKVyxb5dXRY7VWe9usnEtm0cevZ5rrjsAD/9+tfQW+7j29/+Kq5bZ/r8OUwj4rc+/F4+8rt/\ncUnYxgRIJeqWzakKrYbHvfd8k8sP7Ka6UuXc2XM0OwGLS1W++eD32Kh6CEVDqAYJAXEroNVs8u1v\nf4t7v/IF4sAhZUbEsYPndHBaEUnsc/rUMY4eeRbHCRjs76PVrDMzfY6xyZ1sn3LmMCMAACAASURB\nVJrg5puvZXlljvXqIqpqkrFLHDl6lMBXuPbaa8nlcjzzzDP09/eza+dOjp84wcrKChu1OqPjk2yu\nrTDQW0JVIW1ZmJqJIlQW5xcoDQyTzxWJwpAkSlhf30TXBO1Om59/500sVg+gqAYrS1Xc9hq/+Su/\nyJ//2W/z0De/yvv/zV9wQZz+x8X2ttddD4S8/k034IaS62+8AkUR6KqKZVp02m1M0ySMPMIwJIoS\n2o0OlUovTqvFoUNP8cKRFR7/3iGOHTnBZVe8goH+AbwgpKdUYGVtjUceepCxsUF279nDtolJao0a\nYdydaftRhB+16bRcNHRUqdKp1Qlcj9nzZ1leXmS1Os+BKw6wtrbCkSPPsry2yM5dU0zPnUJNqcyu\nHyWnWyhegi5T+IpHxtAAlY7vMz17nnOnX0CRMVNjO9g2OEExXUAZtDi7cph9+/bzyKPfY32jwYED\nr2BwaJiFhSXS5ZemNf4JE3q57N6zm527d/D0sfPs27WHF144TNjs8IUXPs3E4AgHdu3mkQcfwtms\nkypk8Zw265aB73Xb+B3PYWV9gx7LIgw9mq2IUNfRLIMg9In8GNs2u5wcmsB3HHIpCyUOaFVXqa+t\nUSmWiB2PbC5DbOl0Oh0G+3tJGylWlpcRQcKrr7qKwHOpLixjSIHTaDKxYxfrK0tEcYTnushEoX9w\niMyQyqMvHKHjuhSKeXrKZUSrRi5n47XbhAgGB3uZ26whpKBvZISzZ2fYcJqkQx9LV5mZPnvJ+D5z\n8CD79u3BSqXoH+jH8zxq9ToT27Zx4MABrrvpSnTNIggkiioJogA/8qg1NgkSD9M0cZ02u6d2Mjo+\ngSIFhVyJW255HUura8zOzXLNDdfR8SIylRG+9ehB6p4g0zvBahOklub8ycPYmTy9w2NEiUosBUJT\nkGoWJzJZD3UiTccwBQ8cPopMAs41GkgvppQt0mg0cUSanTv2smv3MF++7wsksoiKJHAbvGLfHobG\nx2g2EvwgQigav/t7v8cj/3wPupA899Qhbr7pZj75yY/zrp99FwvzM+zZteOSsR0f6efI8wfpNBtc\nd/WtHDx4CF2D/r4W+clBxid2c98DD9LuhLhu0m2uEl16Zytl43daPPn4Y/SU0vRViqgKxDKHmdbQ\nTEE5W+b8uVnKpT6KxSJzs0fZWF8nl82DhIPVxykUsszPTWOndUhAUROWFuZYWdnA6wR4ns+RI8cR\nEnorvczNLuA6PkmscOUrrmR9Yx1NSXjD629D1xVa7QbtyCOdMuntKVBt19CNPIcOHyaIt6NIn05z\nA0VGxKFHM5IUCj2oiaC3VOKB+7/O1ddcydLy+ksD+EO2lfXzrK7PE7zgs7ZRR1NVhOyWh+qajmHo\nqIrSfaeTmIydo9VyaGw20VSYnZnmxIljyCCHqRscfeEFNtbX6BscpO20KfdW2LF9jM21Gu3NFsSS\nvoE+ZhfmKVdKqJraDcuoNfxOwOzMGdaXV/A7HYgjZBLxf/7hH5CyLQxd4cEHHyCTM1len6Yy1IMX\nt0mnY0KvRrFShADSRZM49FGEiaWlse0M4xPDxEETVXcJZJNEBKRzNqPGOEIo7Nq1i+WVNYSQtNsN\nOp0G5XL6JfH7iRr17z3+JO9/33txnQ5DhR4eeeRRJicnmRgZYuzmYZ574ikOPfIomueTMSzcjsvE\n5DZWW3X6BgY4OztDnCSkVcF1t9/C/muuZHV5AbfTxnMc1Gwa5FZzUhCyuLJCWmjYaZvE93CdNvmM\nTU/WJBQxQtFY7XSYPneOyvAgZzZq7Ny5m1PHXiBtphntGaA+t8Li+Rl2jowzPX0OwzSw0zlk0qHZ\naBJvVFlpd1AVhd6eCl6ngZEyUTSNWq2KRkK742BlMmwb6md+boGB8TE+/JFf59HvPY5MInZNTRF7\nl0ZfCtDT08fVV1/Dz9x5B9PTZ9morjEyPMr4+ASVSoVIdHnVVU0hDiVfveebHD5ylPW1VcqVMp7v\nEMchb3zTG1E0jTBO0FJphKIyODRMT6WXT33qH1A0k8W5Ra695mrWmhGd2OD8YpWO12D3eIkwgchb\nR9PS6JqFjBQ8N4ZEEhoqsaHQkiEoAkM3aXsuGdtmJeiAaZAyMxw8+hzHZw8RKwqx7+E1q9RqLvn8\n9dx559v57Ge/RBRJavUamgZvecs76C8XydsZ3vim1/LBD36ISk+OoaFBWs2XbrV+qe0dd72To8eO\n8dQTTzAzfYbz0zNMbhuj3mgwNz1OoVAklSpR6skSx091VYdkjBAQBiGWaTM+PMjkRD+rays0mw52\no0WubLG6tk7z1BkqlQGWFpc5ffosjVqTzY1NDFWj3W4TCoXzZ88yNNhD3XdRVEF1o05f3xBrqyuY\nhsHM7ByqanD77bfy8EPfAVT8ICCXzRK4HW6++nLGxvtRhIulgyltDMUkk7bZNlJh7thJnJUO2fJO\nDlxxFYQdNpanUSKHQi6FmcnTbLs0Gg7LK1VGJydYnJ/Fd/1LwvapZx5HEuH6HXRFJ44i1tfWMA2z\n2zgVRrSaTYIwxHM9DM3C6QRMTU7R2KzRajdBQlrXaXXaCBUIPaorc6QyNkrsMD7Ux9TwKJadYtuO\nSU6cOsHlB3Yxvm0C0zKxLZ0kSmjV27htl2wqTRR4mIaCpikcOXmGIHD46rcf5Pjxw3SCBlffeAAt\nrVLuH0MzY1KmRSFbprkWMD/3KKrMkFJ11hfrZIwMV992M3aqy6O/utCm7iyRMnvRNZMgCNENk737\n9vDY449x2+23MT45gOP8L6AJ+P9ze8Mb3sTnPvdPTE6Ms2vHPoxbbiWdtek0W5w5eYLDzz+HpSjo\nqonUdHoHRlisrrNt727uue8+bDuN77qYhs7QxDg7LjvAnisvR0pJFEbUG200zWDmhePguYhGk8TQ\n0YSBUASlShG/0cTx2kS+z0D/EMvtFsVSCc8PyWQL5LbncJs1jh85QWdzExEETIwMY1omCt2eZy1l\nE0cSpeOSSEkmnSFt28xXN9BTOqubdYx0jtZ6lUIqTX9vHieKSDSN/vERsoP9VFcW6S1kiFo1vvON\nexkdG75kfAd7R/nQr/4KUsRbwgcacZQgExU1FgSKgqoYJJHCE489x9/9zf9Nq+EjpYplWYjEZ3Cw\nwm2vuQWpgGZ2KyskEgTops67fua9PPPss9x64+00XQc7nydfzrNerzE3t8DybItOACdm5glVm5On\np5ExiCRBjSV+ohFKBbZUooRQsFQV3C3SrUQh8VpkUi5h0CEKEiyRRkmqEKt03BTvvPNt/OPnvoCq\nStY2Vzmw/woOH3qe+XSdkYEB9s7XuOW2a9HUkKRRJ1usXDK256bP09ffy7vf+26Wl5f54he/zLnp\nboz52WcOc9311zA6PMo3v/0IbhAgFIU4SVA0DdMwkJFLJp2mVt/EttLIWEckBovzG9hZk0LeptMK\nOXNqGtvOUakAQrK6ukzKThGGOoMDo+SyZWZnp6lubqIIlYNPP8ju3XuZX15keHwbGTvPs889T73Z\nREhJGPrI2Eanw1X7X0sUdzB1lThySWdMVGGwPD/Dq6/YwfdOnEGSEPg+s7OzbBsdYHh0Ahm08J0m\niozw23Uq+SKx77G5Mkuz3aRcKV8StqVSP6ouOPz8c2QsQCbMzyyxd/ceZs/OI5OEMAhRFY1KpY/N\njQY5q8zSdBXfdbv9LELBiRtoikLg+3zgfe9B0UDRFRzfwXM9to1NohkaG5tVBvsy1DcXeGr1LB3X\nRYYJcRAzNDhCOpXhmbk54tDDsnSEAkGg8c8PPkijWaXe2qTQY1GupNHzkkq/Tf9AiWwmg0w07O09\nPPmdw2zORWhKwj1338eNtxygtr6CPiSZnz9HbSPC1jyydkLomfT399Ny2hiGwmtfdyuN5iaJSHA6\nGy+J30/UqO/cuZdcpsQ9997L2fPz6JaBnbLY3NygVathFG3CIGBweITBke088fyzBKrGwaNHCeME\n3/Uo5wr05LK85rbXEYZJl+s8SdA0nWK5H1B4xfU3cPr8eR545iAjhQJOp83+yUm2DQ6ghQFnTx2h\n3F8hICGdz+LMz7KyVmXb2CQiTLjswBWkdZ2ZU6eZPX0KgaDZapHNpmm2OnhRTOz6jA0Osbi0gm5b\nvOLAZax897vEQuFTn/+f/NYv/RKbC8s0Gm0GenvpzeVpdtqItU1WGnWs0UEqpTJJs06fbbI2f+6S\n8S2UK12aWinQ9TRSgKorCAQyVjAVBd8P+OIXv8En/+GzNBsNlhfnGBiqkMQBoe9y112/yPj4OEnS\nNbrfl9+SgCG4/rbrSGLokzGqbhDKmJH+PiZGhoj2BBi2RiNQ0G1oez5xCJEviX2JF0MYS4IgIgy7\n6u+B/y8zPVVopLU0ie6g2yqmlcZUDCwkKcUjq4Uc2LuL973nXXzqM/+EF0acOHaY/fv2ceb0GZwg\nxLRTDA4Ps7Y+R6lSQdWSHwTrx9xa7Tqa1mXum9qxgz/6D3/I8ePHef655zly5CzNTsDjTx/CDWJ6\nevvw/S79cxAGxH6AFPD8CwdRCcimi+zceRnT5xdpujWqm2uUyz20mg4KCoahMDY2ThD4FAo5DEPl\n0GPHeec77uKee79CHEfcfPPNpKwUfT2jxHFCIwjoHxnj/Jlp8uUCqY116tUqCgkyFrzy8v3EYR0h\nfVLpFMLQ6DTrJLHETqtYhk6lVMTzPRSh8vRTT3PDdR/C72yyuthENWwCp0ZvMU8SJ+ybGmez0SBj\nSXp785eGbSump5Rl387LCbwIGcbUyy6nDs0gOt2Yv0wiYjVifbWBCFVcN0LXDEw9C0aCGznopkKc\nhJiayefv/ixh7GOaGsVCHsd1+F4qQ6vdJIwCUEA3DTaqmxhmCi2yECgoylM023Wmdm6j2awzOzeN\n7wdoslvBFEWCbTsrXHfTFQyMlylW0tgZHV1N0DSNdjNAVWKuffVV/NOZh4n9Ns8//Qzv//m3cnZ+\njaWlKqXeAUbGsjz71DE6/iZZcy+nz5/CMtO02z5ho4ZhSk6ceJ6ZhSMvid9PVqPUzjM4qPOhD/0G\nq/U15hbmKJQKhKHHzu2TnD15klwqhdMK+NKXvkmoatTbDWaXFjANC6SGpaX4uXe+B6/topkKRAoo\nAqGqRGGCjCWRIjgzM8fk7j003Q5+FFMZGGB0YgItCpnaMYoaC+JQEugWcbEIVponvvck11z+SjSt\nSHVpidGxcWLHwU7pbNZqnJs9S8f16e8bZnRggDCOiZKITqNBsVRGxglBHNH2YGZuEd1Kk/gRtWqN\n3l6d2A8ZzfQw49Rpb1ZZWVqkoJr0ZDJsti4tLglw7NQ57v7yP3P7bdeTyegIAbomIJa4bsBTB5/i\nU5/6HMePnaLVdJifn6OnUsS2DdqdOvv37eX9738/Uko0TbvIN39hi+IYO5/CcTw0TUNXFBIZYesa\nUhHd8j1bARlh2AZ+EmPbFgoSrcv/TxSDlNBN6guklCQvchyKBE0oSE0iFUksFeIgQVdBxEDkIFWb\nD/3aL3Hfffezut7E8RyqtTUmpyY5d+48n7/7y7zzPXdS6R8jnd5Os3Hp4RcUgW7qJIlkYXGRkeFR\nLMvmta97Pa95jckj3/kO93z1q/h+yPDwMKYV0263KJfLpFMGuvD50z/9Q0aHBogTnc9/+ovc+7X7\nyRYzFEp5Tp2cJvRDqtUOo6N9/NQbXsfOnRMksc/i0jzTM03mZueoVRvs2LGDTstjZGic//hnf02p\nlGNk3w7W1ldJZ2xefdXVHH3hBWQSUSrZjI4MsHPXJCvVDRRV0vRamIaGTBJ0zcCyLOodjze+/vV8\n6jOfIZWq0de/gwe//RB3vPl1xFHIqRNH6bEUXMcjk+5K8nmdFj2FHF6nfUnQzpybp7aqMzzUj9AE\nzVqTdrOB22zSWyrTcVxQUyimguP4KImCDMFUNWpOlUSJGRjvBxljGQaJjNhsr9FsVElZBm0/jef5\ndLyYMAoxdIFQNEzToFQqs75aI2gqBKFP/2CZXXsnKPdl8GWV/VdOEYQRw5V+0tk0QyM97LtsJ2Hc\nwY/aKKpAKDEyDlClJGMayCjgwP49fNq/l1S+jJQxn/30Z3nT225lZqXO8Hg/9foCk7uKPPrQdzj8\n7CNsn9zJyPA26o06qyvzpNIKHafKu97zFp76p4d/KH4/UaP+mx/9HQ4cOMAdd7yF3lKZtGmRTqeZ\nmZmBUOP5507iOA7zy8uQMmm2O8zMTWOaJlHgIRTBnqsvZ+9Vl+E5DrawiYMIVdWIREgSd0ujQj/h\n2PPPMjA6TK9lUhzYgSV06nWXVqOBJxIcx8HzfHwvIPLhyUcf5sCBA7iug+80aIURx6dP0GjUcZc6\nJElEEPj4CE60Z1BPHmeonGPf1BTZQoEo8jiwcxePHztJppDhc1/8Or/567/GzJmTfPvRh7A1BZEk\nNPyues6FTVVVhKIwPj5+yfiubVb5/X//R/z5f7ap9BTYtWsXxAkrK+tMT88RBw2iWLKxVqVer5PL\n2vSUi2xUlxkcrPDHf/xHZDIZ4ji+uH+/zJ5EigTNEMRxgK6aKFKSxAEi7nK5yEQiNQUZu91ZYgQJ\nkgiJikTbaoEQUnZn/gJQlBffAhmriETpJsviEEPtKqwLoSCSLkNfxk7xd3/zX7nzrneTy1isr6/Q\nbLWY2r2LuZlp9uy7kTvfdgfveMdbueyyPZeM7bmz5zh29ATlUoXJye3Mzi7iuC5PPXmImdkVVlZW\nMIwUoDA7c544TtBUBZlEXHbz9QRejUce/jaVcoG0VaC2WaWvt5dGu87q6hpxHIEiyOcztFpt9u/f\nw+joEKmUyquufiWek+L/+thfEHgunVabwPNJp1LkMibXX/tqTi6c5bc//G/52le/zv/427+hXLDY\nc/U+KuUChiFotmpIRSF0PTKqTScWxDHU62ukTBuEIJ8uMDYyxma9ztmz56hUenj8yYO8+U2vp9I3\nwKlnH8O2VVzPpb1RRbNMvCgmm7s04elCNkcmbfLEk08jjA7FXIFOtIEvGlx5+T6efe45RkbHcFsS\nZ3ORlGmQEBHjoFg+g2M9lIdTlMt51tZWMQ2DQphDVXIoSkIum6Gnp5disZcXnn+Bnt4cN1x/PVbK\nRlVMpBR85u+/wqFnn+P3//DXEVpAvpSi3twEJUEg6HTaaLqGpiu4fpXq5gb5fBZV0/FcH9NSCcMI\nVdPxPQcjleK6my7jyceOUcxXOHbsGLsvm6JnYIjl+Tq6mbC2Nsu11+/jNbfs5/z0GVaWT9ByVti5\nf4hSscjAwAFMXXlJ/H6iwtMf/c2PEAQBL7xwmMDzCIKAlJ2i1Wyh6zop26a/vw/PDzh0+AUa9XoX\nSLVL5vP2t7+Nt7z5LRjEiCTakhaLME2TOI4RQpAkCc2Ww6c/82lKvRWSJEFVVS7ffwARJ0Sez+zG\nCstLy7RabUChWCjg+yFjY2N4nsfTTzxGHEdkMhmcdgsFEEISRzHoBp04QgQOeG0ip41p2vixRsdP\ncKVCEIVYukapkOMD7/05Zs6d4/HvPIKqqDScNkIINF3vyufl84AkDCMOnp2+JHHkocmrKJVKqApE\nUYAiQEhBFMZEUYzT2mBzc5MwDOnr60fTFMLIJY4j7r33S+yYmtoiPovRtqS4dF3/vvtIsRXK2FIA\nEoACXWMsJYnUQQEpYhIlQZJ0u9gkKFKgyLjb7XDxwSUC0b2QFAgkJJCgkgiBFBLUpOsApIZINOKw\nSSqTYXOzzvHjp3nnu96LbuXYbLbRTJvR4Z0YmoHjtKnXqkgZszz71CVhu/fAGBPbtiNQyWZzBH6C\n47g0my1azQ4b1XWajTph6KEKgeeG9PRkePOb30ilp4hlCEwzInS75YuKkiZKVKQaExFgbOkJJLHE\nTtnIOEIoCZoiieMQz1fJZnLUai2KhTJhEFAsF1lamsNx2/ihg+M6XHXlVTTqLTyng+93sCyNQjaN\nG/iEicBxOkjZFSQ3dJ0gDNE0DU3TWJ+t0tPbxz33PcTgaB9BFPK6195CPpvmphuux2vXqdeqrK8v\n4zotQt+jXO7BslK87QN/8rKFp//+S9/gyace5+Sp45jZDn29vViaweLsAlEU01fp4/z0NDNHF9Cl\nhpAJbtAiVl2sHo3/7TfeSzts4gZ1JicnaTbqpG0LTaFL05uEmLpFysjg+m08z0FTVeJEEvghuWwR\nJSly3333UyynuPnWV7PZWCGTManVq4Cg1FfG931Slo2pmThtF0MzCT2ffKmAYetsrK+AlMhEp9OS\n9JUm+eUP/gahO0IUCQYGxvnQh38d1QpYr54mlXXI5Q1ISiwunUc3IgaGyiRxQm2zQ1/vKK4j+eAb\nfuWHYvuSRl0IMUyXdreP7uv3cSnlXwshisAXgDG6DUh3bZH3/EjcyUIIuX18gmKxyK5du+ir9DM9\nPU2SJFQqFRRFYXr6POfPn+8aW0WiKMrFmK5pmvT09OD7PsWs3U1aRl3BZkVVSeIYYMtR2IyNj6Nb\nJp7vk81m8VodTE3DabXpyBDX7ToV3wtoNdt4fsAtt9xCGIasrW1Q29wkCDx0VYAEVRWEYYBUdWJV\nQYl9DBmjC4mi6NSbHjEam60G5tYLqmsaJAn79+1navsUJ0+e4onnn6HjdFAUlaGBPnZNbcdKpXj8\nqWeYX1wC+NaPi+0FfCsje/B9H01VUbrKIkRBtKUkn3SpbU2LbDaLrus4Tptt2yb4y7/8S3bv3o2k\nK5WWJAmKoiCEuBhXv/A/JLI7c7nQcpxI2XV63acgUqytxGqMJCaJI+SFM6SCIiQK/3oMds+WXc+A\nJAa51SyjRsTS2TrfBplCU5r4nkvaTtPpdDh3boYP/vK/ZaPWZH1lvrtiA0qVMUbG9mDoGk9+926A\n0y937BbKFqCSStkUCxXiWNJudVd7Yejiex6qAr7blSscGChw683XYRoauqEjCVAUlzhwMbUMSWTg\nxRLDUolFiFTATmVwOz6maSGjiER2NTd938U0bJJEkM0UWF/viqfv3r2TxaU5dF0hk4KVxRUSCbqZ\notJTIQh9bNtEEuH5Hn4g0bRulYdEINQuyZ3jdpCJxFn3kIpKT/8gn7v7bnbs3EmhnOeVr7iMxx97\ngrUNn3bbQQjJT73xRvbvG8JzAj7+ia9z5OjZlzV2hRDyT/7604xv28bswgyr1bNYZqoryqIZbGxU\nuf/r97G2tkZBTdGu1zAthbZXJbYCfvW3f4Gx3f1YOQ3Hr9NstlAF3fErE+yUxfr6Ghk7QzlfJow8\niqUczWaDMIgQQiMOQdPKfPrTn+Hyy3exc9c4lq0ilJjA9zEME2nD5kadwA1Q0RCxStbOs7GxSalc\nptqqomsKPeUCoR8jpEkSGFSrbf7qP30Oy+hBScpEYZq73vGzvPKqvZw6d5Bi2cIyTey0QrU2T/9A\niU7HxdByeK4gjmJ+9W2/eMlGvR/ol1I+L4TIAM/SpdJ8P1CVUv6ZEOJ3gKKU8qNCiD3A54BXscWd\nDPwAd7IQQu6c2kGSJNRrdYgVEN3wg2EYuI6DpulIJJoqujNNRenqD5rmxdm4ruskcYiuaghFdHVF\nt5byURxjmd0a9f7BQYo9ZZZXV6iUe1hbXkGGEdlUGkcJEChEUUSn43ZnmAnccMMNmIZJlAgeffRR\nQt/H0DUUITF1A5nERIpAqiqKjLqczaZBGESoqolhZ1nfWEZVFVbX1lGEShiDrptEUczQ8DC9/UUm\nJiawLJOPf/zvueuut/PYY4/TbDaYmZkF+OiPi+0FfMd27SOJJHGUoKsajuOidr/rBrKlj22n2dhY\np1zu4c477+SXf/nfkMkUEEIhjh2UrWhLFEVomraFTXLRqGt0D+hWxXQN8YXvJJIgVoAYKSOEjLvO\nRCqAhpQqiAR+wKgDW45CigSpJojERkFFCI+YBkKAkHmQORTLRcYBGsnF1YgbhPzxn/5H7v/Wg6DZ\ngGR17jTp/CCB28LrVOny0b28sds3XMT3YhCCOASh6IR+CCiIxCMMPBIpKeVtxsYGefVVV+I4TVqN\nOkEUk8ulSJIWQkbEoUDXc6TSOfzYQbdUhCJQFA1Bt2Flc2OdVMqkXCrged0SxihMsFM5klhQrzcY\nGx+lXl+nXC6ghA1URaXVcjDNNLVGNyGoagpu4GCbJqEfYVkpsrkCYRjjBT5hGJKyDBIkfgOMVJpa\nx6Xc389X7/kaA0P9LC3Nc/lll4GewTAVrr7qCv7sj/8bn/jUn/OVLz2AZZj8xX/++Msau0IIuf3A\nNQRRQqGYZ2Coh1hCvdlkfn4B13HRFQ1FCGKniamDGzXxwiZve8+bueWN16OkIsy0ThR3nWzKMkii\nmLSdxu04xHFM2rZRUIjiAMNQ0HSNVquNphq02y6qksM0LaLEZWVpjkpvEd/16HScrqPISFRFwzJT\nFAtlAscnScBtu8QS8qUCfuDhtBu4jkcxV6anPEjox3z5i/dz/71Pkk8NYxtjRKFFqVLhvR94N2Pb\nBnE6a/hhh9XVBSxLw7bT9FaG2LFjL4ee+S4feOtdl2bUf+AEIb4K/Net/SYp5eqW4X9ESrlLCPFR\nQEopP7Z1/P3AH0gpn/pX15E7tk/RbDYxTRMNHUVVieP4ouFQlK6hjeOwq24eRWTSGQzDAMHFxJ2U\nErEl3sCF37PlIECgAh2nw5XXXEP/QB/ra+ucPHqMbMomDkJis8tWGAYBUZwQRTFCqOzevZskSejr\nH+WRRx/GUDUQktD3MU0dXVHxo5De4UFuvvF6MimLr3/ta6yvrxOEMbpuYVoqQgiCICAIJQuLywhF\nA0VFJiCVrp6irmk0avWu7mKzxfadOzhx5CjAwI+L7QV8x3ftwut4W9UCoCgqIumy7cVRTBS7pNNp\n9uzZyx13vIUdU7tQVQMpFexUGk1PCMIOpmkiZXelBF3cu8ZZkrgx0dY1E5kQJQmxlMRJ14ArKEgi\nSAJIEsRW2ASpIdFJun/Ri58bVVVQlW6nplAkUo/RRR5TM9FUD1Xv6k6qJpvymAAAH49JREFUFBFJ\nEc90kVGALiKiLW3KdquNVHROnZvhS1/7CsdPnmB9fol0Pk9ro0oUhReM+ssau7/xS7exslqjVquz\nWa2RxAlCUdF1g/WNFoVikW3j4+TzaSxTo1pdw9LVbsOKqZHL5lhZWUUKhTCRqKpBJpcjimJM00QN\nfZZXVml1OqSzOQzDQjUs2h0H3TAIozqdtkMcJRiGiYLK1PadrCytUiyWGOrTuBDGa7UcFE3HNG1M\nK4PTcYhkjOt5CAQKgka9jmEYaIqK73uk02nqUYSq6+RyJcIwQlFNDj13hLNnpumplAnxGRoZob9/\ngAfufYjhiUGOP3+KfVft4+mHnnlZY1cIIYd3DaPpJomQaELS8TyEoZNK2zQbLUQEkR8S+B5+5GHa\nKj1DBd7+rp+m5W5y8LknkTJG0wRT26coFgqEfkjg+8g4wTRMkjih0WpipXTS6RQp26SQL9FstllZ\nXqfR9ruygKogm02hAsV8D5XyAIsLi3iiRhRGjIwOkclkEKogiiKOHD3CtolJioUeTFPj5InjNGsN\n9u29jMAL0TUT2yxw/9f+mae/dww1KVDID5MrVah3WghNMDrSw66dexkeHsU0LU6ePMmZM6eZn5/F\n1iWnnnn2hxr1HytRKoQYBy4HngT6LrQBSylXhBC9W4f9yNzJURJjZ9KEYYjQoN1pdgESCp2Oh5AC\noQq0rdreom0TRRFhFKFsJewkkEiBSLoJuAvFGd24O1slZD7ZXBY7ncH1AhIJ/QOD7Nu5m5GhYfKD\nRVKpFGEQEgQRa+vrNOotWu0WYRCSzaQp5vN4bocwCLBNnSgM8aSHYZlsrCxx9xf+kR07dvDGN72J\nu+++m7DRICGg2QrJZNJ4YUCSQLlcwHE8/CBECIUoCrC07osUBgG5vgr1zRr6FsfDy8UW4KdufT2H\nDx+mVqt1dUMR3dWMYZJOpykWi0xNTdHb20uz0eHUqdPYto1t26RSqe5LrmmEQVcODbpOtLt3V0TC\n1FClRCQJipTIKELdcspJkmz9BgMpUxfG0Pc9o6Io37d3jbp6cVdUga53x4Cu62haBiEqF6/VPT73\nfdd0XZfeAa0bmiuV2bNjF0ePHuXf/e+/yy++9wP85V/9BVEUXhK++8YrbOvNYNu7kRLiWGLoJqZh\nUqt7BGGAYejEkU+juclVey7DczpEoU+SxGi6ytTADprtDrphsri0jGnFBEGIH3QwpGTfWA8dN42m\nGVvOMqLX6jaybdQFlq3huT75XApVNYndBmlLoOGzvrxCEkdouo7r+kSxAKFSLPWQJBLX8+i4HSzL\nwtB0KsU0cRxj6DqtyCF0miBjahtt3MYmppkijCRjAwUMBjl9+hxBLAjbLmcOn2RzfZNKTwbP9Qma\nrUvC9q13Xk+z1SaXzzE/c4ZcsUggwPF9fK+Ahsq5E6epdXSyegY7Z2JYgk99/nOEccDkthE810VJ\nEp57+gRJHKOrelcNCYVUyibwAyIlwXXaGKaKRKIoKp4bkLIyoGm4nottmXiOi0gULH0R3ztENl1A\nS3VwnDanT86hmQpDY0OsrC4SxQHzCyuYWoowDPBdjySRrK81iYIE34+ob3QoZYv09KRoN5o02qfo\nhHNgGFimzdpGk1p9jfA7GppqYRg67U4VoXq4zks3dv3IRn0r9PJFurGwthDiX0/xf+yMa7FY7Aoq\nKAq6ppBOp5mbm6PRaDA43Eel0ktfbx+xlCzML7K0vASAomtbNxTESQx0KyOIJaqqbsWHna2ZukIq\nbRPGEZlMGsM0SVkWGgrnz59naXGJUI8Iw26i1fN84jgh9CMSKdm/fz+6JqhvrpMyDGQUoho6iSJ5\n1RVXcvtrbqda32BtvYppWTz15JP81m9/BM91cTpt1qqbtNptms0mjXoDz/XQdR1D02m1WmSyGTaq\nVb5x/7d4za238IY3vI7f+/0/4Pd+6yO88z3ve9nYAvzu734UEFskVxIp/yU2rmk6YRii610N1q5M\nnYKiqBfDJ4oitoytetEYCwFCKFuJTMlFL/ri8vUXxd1fnAf5gTp3QFUUxNYzXVh1JXG8FcbpXl43\nvt8R/MuzXHR8PzCuwjC8KL1Xq9X50K//Kn/7t/+DO+64g7/7+N/g+96LT/mx8c2rIcWChee2CYKQ\nSqlEEgfEkcdobwanHdJqV9F1FdUIiBuL2LqKkTYgUclkbBQVjDBB0UOKYxWiKAbFJkli0rpFHEcE\nUZp6rY5hWRQKBTqOR6PVxJYWdrqHMIoRhkG90UJRAvI9Np7vgxegWzpJEiNViZ3L4PkBOQs2NxtY\nmoJdtFAATZPEoYuhQMrUGJoaxndd3CQhTnrwXB/XDxApHT+IKE30sW2wwMZGh9Onp5mZ36Sc1vCq\nqwgpcdeXLwnbK26fIpNN0ek0eaWcQigC3/NZXV3Ftm2SJGHHKyosLa7Q3z+49c5KoijCtjO0Wx2E\nELTbdXL5PKrazQtpmko2m0ZRFZJEcurEaRxPYXL7KMViAV038b2YKITQF5w4cZrBwQHCrdDv/Pws\ndpzw2tdehVBgZWWZOI4YHx/l1OnjvPUNb8BO29Q2G6yubOK6LsvLy2QyGSYmJtjY2MDzfezIoLqx\nyZWv2M3C4jLpVJrl5VUmJ6dwXBePGsNDA2iaydpqFV1TqVYtLKuA47SZO3bmh+L3Ixl1IYRG16B/\nRkp5z9bHq0KIvheFXy6IUP/I3MlCiG5zg6IwPDjOtskJlpcXMU2dQqGAYehsVNc4dfoMUdJNjkZR\nhBTKVuWb0l3eJ2wZGImm6gghKeTzZLMZSqUSuayNv9XQ0mo1+frXvo6ME3QhkFFCpMddQ4UgSSRx\nHJPN5IiiiJtuuhGn2WJyvNv84boOI8PD5PNZprZvJwp9KuUyuVwORdMZGhnm8OHDXPWqK8nlMgyM\njgAKMu4WZCtCEAYhpq6hKCod1+N3/t3v8553v5PdO3dy6PkX0FSVe7/29QsYvSxsAf7mb/9bt6QQ\nyY033MS1112HrulbnZsCKbuhJk3TLhrIbggLEJIkkS869oKhVxAXmOLkBcMrLu7dV1iS8C/VMP96\n+34bLP8lYibEltMwvu/7OAkvzuCBF60A5MXzvv/6Esvqdr+GYcjP/dx7uPrqazh27AhHjx65GEa6\nFHw/f98RVK2L1b7JCrlMmiAMCcOQRquOqii0mzUK+SyZtEmnXSeXzeAELpqi0ZJxl1XSc1FDjWKx\niOt2HVHHdVnf3MSyLHp6eihkUkjAc10sNSZVzNKbT5PNZfG2wisFs4BqmoSxJJYmKSVNEseomoYE\n4qRLqtbpOOzePkK700a3dGSSEATBVszZJgojmmsLZDIZ8vkca2trpNMWZNOEUYLvJ6TsNFaqB39U\n8sLxOV53wwH6KwXOza+zuHGG3r4BTs02Xja2X/nkQ6hqd0Kx88AE+67chpYyGRsdJp/PEwQ+I8MD\nxFE3pOj7IaVSiU7bYW5ugYmJCWr1GnEUYds2pmXiug5RFFIo5KjVapimyWX799PuNEjZBuVygXbL\nIY7ZSpSmedWrXoll6URRRBSHPPvsQRQhKBTS3fxGMYOma0gke3fvplGvEwYBTrvD5LZxhBCkbQtF\nUeitlBka7EdVVbxGncGBa1hdXedV1+4jjrphsrSdxvUCgiRA102khO1TkyxNb7I+ewLfjTHU/3Xc\nL58Ajksp/+pFn90L/DzwMeB9wD0v+vxH4k5uOy1830dVFA4e2uSZZ59FVVSEUFlcXML3A1KWhZSi\nW5+sZ9EUFQVBKpWip1Qil8sx1FehmM9jbc1mDMPAMLpSW416nVhRaHc6PPbYY91qEAFSFSRSEisJ\ncdwtURTiwuxUR5KQyJi1jVUy/0975xpr11Hd8d/smf08+zzu26/EcYzACYmEgPIoVFRQIVQkUlGQ\nKFRqg6qIiqqlVcWjQk0q8QHU5GtR6UOirQpq1YpWqioKIkmLkAgtsRNDAonzILFjX1/7nvd+z/TD\n7HN97djXbxw7+y9t+559ZvaZs87ea9as+a+1fJ83v+1NvPWtb2U6nVKWJbp+GKgLKisp0brCVy53\n3P56sqy0k462m4R2BeFZi8GFytitwC/9+QPcuns3v/HrH8J1Xe7YdxvJZMriwkao9SXJFuDeP73P\nKjwBZVlZq1gIKl0zVoTC90FrqKrylMUrrCJ3XadWsgJjataiOUUjNxv/bDLYDYBAiTOta3vocwVz\nzliM5pSFLoSw84ujTrPyZ5vhmyeazdBab9Av77nnHl7/+tfzwAMPUBQFUkqSZMr9999/WfL92F1v\nJwxDptMpRZmTGYNRHp4fovOCwPfx4zaB79tlvxeijUEYg1AuRimEq+jFXRzhUJoKIxWF1hjlEnSs\nK2ecFUynE5SrkMLeQwaQyZDJIEO5Pt3YoxIORaXpLi9QakMyXCfwY9I0QTgSRyk8z0MsdBiNJxA6\nCGndae0gpCwKfFdSSEMwHyOlpMqn9FoeylMIRzKeTJlbjHE9j6rM+dt/+x57b+7x2x98E6PxlHe+\ncSdGpyz0NlLvXpJs3//Rt9LuBPUK07Uuqw3joiRJbI3hdidmvd9Hm4rh8CSDwZCl5R6OowkClywz\nTJMx2lQEgctolJBlU4LQBTRllYMoKUvN2toqQRCS5Rmu8uj2PNZOnKAoLXOs3fJ51y+/pfYMGPvs\nG4U2Gl0ZVlb2kqQJvudbhozv43kuccdnx/btHD58hKXFRfIip31LhzwrWHBCPE9TlhonyxlNx/Tm\neoT+MsdWV1latG7Gbdu6vPaOJYwx5EXGv3z1m+d4iCwuJJ/6O4CPAY8LIR7FPsZ/glXm/ySE+Djw\nPLZa+EXlTt61YydOnRMjmUxYXFxECMFgOGT3zTfjui5RFJGkKQsLS9x6660Yba1wYawCFoCoSqy5\nforWmCQJQgj8ICApSw4dOsTS0hJCCA4csIVxTa09ZspuhpnCdj2X4WBIZ2WFsigYjUb1j3lK6VRl\niVKbNhDLgrLSKFdbH7CUViHqYiN4ZyaORw88xre+8yB79+zh47/7SQA++Yl7uPvu3+Lz9/7ZbDjv\nuRTZAggHjLGc7tkYhQA5s6o32hnLHtpQ4DN3yam1s/U5nm4Vn80KP/PcqYlipqDPNdpZM3H6NTat\nBM5s97LP2PSe53l897vf5Wtf+xp33nknb37zmxFC8IUvfIFPf/rT3H///QghfsIl3rvjrGIwGdBu\nt3Bd38pVOZZhFLjIIKAXt5GOQzKd0Oq6RKHdE/JDH+FAMk3QVUllNBhB1O4SBB6j4ZiytN9hfX2d\nMO7Q63ZIkim9TpuiKGhv6zCsqbdI8JVHVlYoR0BVEYcheZ7RacdMJmMCP8AYzeqxo7TiFq4SuJ6P\nqemelTGkyZRW1KISAtd1GSeJdY1KB4NhZWUeBAyGQw690Od/Dx5h10qbP/jCPyOE4EPvvY273v1a\nvvy1H8zEdEn3bjuO8FxJlk5xpUe7HXOyXrlk6RTPlaTJhNGwTxy37QqlqFha6lHkJc8//xSLi8v0\nOjGT6ZjJZJ2y8Ah8jyBwLWkhz6jKDFPlVEJSFQZT2RiK0XBMWWSkaYKUEj/wyLJ+7RKs6PZ6ZOkA\nA7TjLv31IbTbSATJZGqfNVMwHo1ZXpzjpSMvEPgeg/4a2ljqa55ltOIYPwyQRUHUDpHDIcp3GIxO\nctNN2yiKnKLMiQK7UguCCMeJt36AuMbBR1/5yy9vWFlVXtDtdknTdIPVMrOsKqNxlId0HHzPx3MV\nRhvQNr9ClWcYXdW+YrVJeVolVmjDj5/4MZXW1nLXVuH6noeUCqEclFJ4rotSCkfWCa0MPH7wIK+9\n9RaMMezbt28jCGdmrWM0SgpbIk4qHOUihDzlJ2ZmxQrAIKVrOeNiRtqro0jrQCmwS0ow/OK73n1Z\nATJaX+xve23uhcvF+e/hly8PpHQvS7Z//8XfJG61qHRBFIUkNetmfmGOUZIxGY+RjnXP5GnGeDwh\ncH2U6+KHLo5jOfjSEUgBSgnyNK3digpHhSTTCe04Jp1OkBKqsiBPM5TrgLLusU67S17oOlEbKNen\nKEpcCUWRE7dtfpM0z2l32kwS62+2YRwuNkoMPNcl8G3RiHQyoSgKcjRZYb+f8lyyPCfNUnDsZjSp\nZmF+gVYc4/oBCIcgCDnZ7/PBT37lkoOP/uG/P890OiQIfLS2k9t0OmGxtlzLsmQ0GsGMRGsMKyvb\nWV9fZzpNqSpNp93F931LzdUFJ0+eoNNpI6VgPB5jjF2JG2NdtlobwjBAGxs57XseWV5YxVpkgGHn\nzh0MhwNLo9aQphlxbK3uNM1oRR1OnuyD0Ch16rl2HGeDzZckCQ7SRhgried6eL7VO1mW4SpFNknx\nPA+pJLqyG/pZnrK4uEiaZXz4nVsHdl3TNAESgS5KEAI/8BmPx6gzIxaNqeliJUK6YCrSJMeVNleF\nFAIlJcqzro1KVwSB9WOlacp0mlAJQ5om7Ni+naUFmy8Z2FCkQlr6nLWsbTTdzFL/lV95N7fs2sna\n8TUMhiRJ0PUEYq8BCOvvF460/n7hgHCoqgpdVacF7mh9ihoohNjI3jfzFzuOtYqqOnjqcmDM6crs\nTGv3QrCVRfzzwqWM+4wrXJFxbEYvDqmqnDjw8BR4LQ9tNMP1VbRRyKqyaSDWB7iuR6QU7TjCaEOV\npyRFQlkUKOWgHIGSNtVBHIVkeUlWpDiUDE4cxZXCKgABc3MxVVUwkg46L1ld7yOMIEsLWlGMlD6+\nF5AmQ6R0GI5sgeusyOkfHhDHEXEcU5Q5Xr0S7vf7NqFaXqGUJPQDlLJxGH7kMBgOSNYHzC30iDtd\nitJmnXS9kCiaQ7ke00lCXub05iIcJ7os2foqpDUfUBQ5QdBiMhmzOLeE67icWDtBURYsLy+T5VNa\nLbtfNlzv4xiH0PPpdKwLdm3tKEEQ4roODiWjwUkcxwYNhmGIchyCIGY4GKGUR+CGJOkY1xFI4aCE\ng3R9hDZ0e11OrK4Rx22yLKEqFEWuGZcTALavbCNNc7rtFr7vIhxDlmVMJhPcICBN7cZ8GAS0w0Ur\nP6WYphN8z6M/6NPttEnThKWleUajkc3madyawJEzHExf9kyfDedPJHAVIY1A4iC0ocpLHARFmpHX\nB9pQFaXlQ1elDZVG47mKPE85+KPHwZRUVUlRFgjHzuq63iDLssymBRCC2/e9jtfsvZWdO7Yz1+2i\ny4pDh57Bd108V9moS2HD0quywFWSwPNoxy1GwwHGVCTTCRiNdGy7J558Et/3Nhg8WmubaTBNyLJs\nQzGftsm4yb2x/8BjmDqQZ5ZbRZ/T6Xzx2MxCudBjhoceeuhl17gYzPpfKjb3P9+YN2/Uzo6HH354\n0+vZnsmp43KhZIjrRvT7Y1ZX11k9vs7q6gmqUuA5Lu1Wix0r29i+bYXlpQWWVxZxPYkRFQefPUGr\nu0zUWSBozeNHXZARx9ZGHDsxJi0AHKRw2bbjZryoB14bt7VA7kTs/1mGg08r6uF7Me3uAq3uHEGn\nyyDLODYcUEqFli6OF9Lq9NixfRd7dt3CyvwyB584Rsv1cUzJdNSnE7dq48jFaEF/MEEbm+BqNJwQ\nuG168QqyipFFxFNPjVhobWOh0ybyHdLxSRyTYvIho/UXyMYvnU98W2L/95+mLEBKn6MvrVLkmkF/\nzOqxE3h+iKdC0qTAQXF89YQt/FETKYSQPPI/Bxn0hwShR5pNWFs7jusq4jik220zv9AjbkcEQYQx\ngjjuEYVt0rTAdX2e2H+YOO4R+DGBH1OVcGKtjzGSPC9Jk5KqcvBURFlBWcJ4PGU47FNVBd978AC+\nFzIeTdn3utsRSG6+6Ra2rewgbnUospS1Y0cZD/u4QjAZ9VnoxWTJkLjls/+Rp+l15zAa0qTgpReP\ns742xnViRv3zUxqvqVLftrzM/Nwc8705u9yQcmOTa/awKqXwlMKvq53oqsIRduBP/OSnNnii5jjP\nlGOR5xtuHGNsbnWjDdPJBIEgDAIW5ud57vmf4Xuepb45DsqRG3xoz/U2al5WRUGWJFRFQZlnFFlG\nVRbsP/A4eZZR6YqiKNB6pmBO+a830/ngVOCO1pr9Bx5DC6gwFLoiKwvSIievSqor4Ao5m7I73zHD\nQw89tKXSPx+ulFK/lInJGMODDz646TUYI047LhfjSR+jc4zRTKcTVldXSZKUsih49rnnOHzkJY4c\ntUnFjhw9ymQ6BWELtjxzZEgrChGA7yqiMML3PFpxTK83RxSFtctOk6UJYRjYicmxcQaPPP4s2TQh\nTxOiwMN3JcJUdFohoa/wlIPr+fhhgOMIkjRjMrHRldMk4+Aza0ipyPKM4WjIaDggzVKbMybPyLKE\n42urHH3pCIP+SVZXj1HkGWWRE8ctjq3ndDsdJumUwcC6MyeTCePJmLLUBNH5/b5b4acHDuM5LRQB\nvdYSRWLwnRamUCgT0onmafk9BicnLHSXWZ7bSS9eQFQ+8+0lDv3oGI528WULZXwWustEXozCpx12\nKRKNo11iv4c0Pp1gnrn2Mu1gHpMrnnrsGMdeOIkrWozWU5bndrF7x2uY72wjcnssdLdz08peluZv\nYj7exsrCTuY7S+zadgu99jxHnhkxWk9ZWdjF8SN95uJlsomB0mXt6IBeu8etu/cSBRGhH7B3916o\nYK4zjxKKpw+uQqUoM0ErmGPP7ttoBfPEwSI7VvacV37X1P2itcZz3dMUn+tIsiyz7AVHWutWCpSv\ncISD0bqmKoW1D1xuUOK01lRVRVmWGxS4NE1Rrn2Is8xunkZRZH2UVYnrSoS2VrRScmNiMVQoRyF0\nRVUZHMcugWeJwuyHGqqypMgFUrk40rpXyrIC4Wwkv9pMC6x0VTNPBNpoqk2W+Wz8V8vNcbYNxa1w\n+W6Py8eVGcOVt12UU2KMYHmxh5QLVNUuqtKmrZifX0EpRRiGG8ZFUeQoZX2nVVmSTEY4wpBMJ/Sz\njG4nZmF+HrC+c0cajKg4OVjD92xKjMl0YDOQVgWRb/eAykozHQ5Z7PVIpxNOrB4lL0pau/fg+RGu\nFzAeTzj84hE8z65Is8xGMYdRaCcKIVC129C6/xRhFDJNhnTbbaKog0DiOC533rGPf/32/3Hs6IsM\nh0M67Q6BHxBGEcPxhMFoRJIXlyXb23e/nQ+87VOX3P/7O0/y4Xd97pL7P/nwfdz9/vsuuf+j/5nx\n0fdcZP9NFRYf+Y/7eN8v/PEWjf9wy0tdU6VuN4UsXc4RdjvL81zsBr6yFriU4AjKqqzLgVkudF4U\n5GXBNEsRho2kTTMlUFUlQjjWHaNLyrKgKrX9vNrH6khJkmU2xYARCGFZCFJK6xapDFJJG0gt5EZw\nTlXpmv4okcrFCOtL18YmtDIb360OvNl0bvaHqaklZVHa88JupBoDurTBN1caF6vUG5wbjtQURcLT\nh18gimK6nTlAUJQV7bk5y75SkpODvk2SNbFZE7Mso9/v0x+sM9fr0QpDJpMJGkOl7eZmkWcoBe12\nCz9368m+oNvtEEYRcSsinU5JmTI/v8BoNCJLM1zPZa7TRfkeSZYRt7sMhyNUELJj101EUYCpNFId\nZn0wxEtTHOnQjtu0ei2SJMVg6M11MMYQhjZfUJFngEOvG3DoqZ8yHA4I/D2krsdkOkW6LkEcM7ew\ngOt5+MHl+dQbXB6uKfvlmnzwdYbLYWhc6bHcaGhke3VxqeyXqzGWGw1byfaaKfUGDRo0aHDlcU03\nShs0aNCgwZVFo9QbNGjQ4EbCpVLGLucA3gc8ia0885kL7PMccAB4FHikPjeHra7yE+CbQHdT+78B\njgGPbTq3VfvPAU8BTwDvPUf/e4EXgR/Wx/u26L8L+A7wI+Bx4PcvdgyNbF9Zsn2VyPejjWyv73v3\n56rM6wE6wNPYMngusB/YdwH9nsFWUdl87kvAp+u/PwN8cdN778Tmfn/sfO2B2+ubQgG31OM7W/97\ngT86y9huO0v/bcAb6vfj+sfad5FjEI1sXxmyfRXJ99lGttf3vXst3C9vAZ4yxjxvjCmAr2PL450P\ngpe7i+4Cvlr//VXg12ZvGGO+C6xfYPsPAF83xpTGmOews2Jxlv6zcZyJu87Sf7cxZn89ljF2lt11\nkWN4y1k+ays0sr16soVXh3yfBPx6HI1sr8N791oo9Z3AC5tev8gW1Xs2wQDfEkL8QAjxO/W506ov\nAcvn7G2xfI72Z45pq4pCvyeE2C+E+GshRPdC+gshbuEcFaMucQznQiPbqyfbs13nhpZvI9vr8969\nnjZK32GMeSPwq8AnhRC/xMvTCl4sP/Ni2/8FcKsx5g3AUeCB83UQZ1SMOstnvhI4pY1sry6uO/k2\nsr0ovKLu3Wuh1A8DN296vWX1nhmMMS/V/x8HvoFdghwTQqzAyyrYnAvnan9BVVmMMcdN7egC/opT\ny6Cz9hdbVIy61DGcB41sr55sZ9d5Ncj3KI1sZ2O67u7da6HUfwC8RgixW9i6ZR/BVkU5J4QQUT2z\nIYRoYXeRH+dU9SU4vcrKRldO93Wdq/2/Ax8RQnhCiD2cqspyWv9a2DN8EDh4nv5bVYy60DFcDBrZ\nXj3ZwqtHvp+gke3s/PV37261i3q1Dix16SdYp/9nL6D9Huxu+KPYH+2z9fl54Nv1tf4L6G3q84/A\nESADfgbcjaUNnav957A7yzPq0dn6/x3wWD2Wb2D9YOfq/w6g2jTuH9bfe6sxn3aNRravLNm+SuT7\nqUa21/e926QJaNCgQYMbCNfTRmmDBg0aNDgPGqXeoEGDBjcQGqXeoEGDBjcQGqXeoEGDBjcQGqXe\noEGDBjcQGqXeoEGDBjcQGqXeoEGDBjcQGqXeoEGDBjcQ/h9kw7d4exKcGAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f65db0f0310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_iter = mx.io.ImageRecordIter(\n",
    "    path_imgrec=\"./data/caltech_train.rec\", # the target record file\n",
    "    data_shape=(3, 227, 227), # output data shape. An 227x227 region will be cropped from the original image.\n",
    "    batch_size=4, # number of samples per batch\n",
    "    resize=256 # resize the shorter edge to 256 before cropping\n",
    "    # ... you can add more augumentation options here. use help(mx.io.ImageRecordIter) to see all possible choices\n",
    "    )\n",
    "data_iter.reset()\n",
    "batch = data_iter.next()\n",
    "data = batch.data[0]\n",
    "for i in range(4):\n",
    "    plt.subplot(1,4,i+1)\n",
    "    plt.imshow(data[i].asnumpy().astype(np.uint8).transpose((1,2,0)))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Next Step\n",
    "- [Record IO](record_io.ipynb) Read & Write RecordIO files with python interface\n",
    "- [Advanced Image IO](advanced_img_io.ipynb) Advanced image IO for detection, segmentation, etc..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [Root]",
   "language": "python",
   "name": "Python [Root]"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
